1
|
Zhou W, Huang Y, Liu J, Liu Y, Liu Y, Yu C. Identification of ANKRD13D as a potential target in renal cell carcinomas. Int J Biol Markers 2024; 39:149-157. [PMID: 38449090 DOI: 10.1177/03936155241236498] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/08/2024]
Abstract
BACKGROUND The correlation of the expression of ankyrin repeat domain (ANKRD) family members with renal cell carcinoma prognosis was investigated. METHODS The GEPIA2, GEO2R, UALCAN, GDC, OncoLnc, TIMER, PanglaoDB, CancerSEA, and Tabula Muris databases were used. Twelve ANKRD family members were identified as having overexpressed renal cell carcinoma samples. The ANKRD13D was identified as a renal cell carcinoma-specific target by cross-referencing the multiple survival databases. To clarify the role of ANKRD13D, the expression of NAKRD13D was analyzed at the single-cell level. RESULTS ANKRD13D was mainly expressed in immune cells and positively correlated with Treg cell infiltration. The expression of ANKRD13D was also positively correlated with PDCD1, CTLA4, LAG3, TNFSF14, and ISG20. The overexpression of ANKRD13D in Treg was confirmed using reverse transcription-quantitative polymerase chain reaction. The structure of ANKRD13D was predicted using AlphaFold. CONCLUSION In conclusion, we identified ANKRD13D as a key immune regulator, and targeting ANKRD13D with immune checkpoints blockade may be a promoting strategy for renal cell carcinoma immunotherapy.
Collapse
Affiliation(s)
- Wenqian Zhou
- Department of Nephrology, Tongji Hospital, School of Medicine, Tongji University, Shanghai, China
| | - Yonghe Huang
- Key Laboratory of Adolescent Health Assessment and Exercise Intervention of Ministry of Education, College of Physical Education and Health, East China Normal University, Shanghai, China
| | - Jing Liu
- Department of Nephrology, Tongji Hospital, School of Medicine, Tongji University, Shanghai, China
| | - Yiguo Liu
- Department of Nephrology, Tongji Hospital, School of Medicine, Tongji University, Shanghai, China
| | - Yuqing Liu
- Department of Nephrology, Tongji Hospital, School of Medicine, Tongji University, Shanghai, China
| | - Chen Yu
- Department of Nephrology, Tongji Hospital, School of Medicine, Tongji University, Shanghai, China
| |
Collapse
|
2
|
Conway N, Chisholm O. Building a Competency Framework to Integrate Inter-disciplinary Precision Medicine Capabilities into the Medical Technology and Pharmaceutical Industry. Ther Innov Regul Sci 2024; 58:567-577. [PMID: 38491262 PMCID: PMC11043185 DOI: 10.1007/s43441-024-00626-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2023] [Accepted: 02/04/2024] [Indexed: 03/18/2024]
Abstract
INTRODUCTION Integration of precision medicine (PM) competencies across the Medical Technology and Pharmaceutical industry is critical to enable industry professionals to understand and develop the skills needed to navigate the opportunities arising from rapid scientific and technological innovation in PM. Our objective was to identify the key competency domains required by industry professionals to enable them to upskill themselves in PM-related aspects of their roles. METHODS A desktop research review of current literature, curriculum, and healthcare trends identified a core set of domains and subdomains related to PM competencies that were consistent across multiple disciplines and competency frameworks. A survey was used to confirm the applicability of these domains to the cross-functional and multi-disciplinary work practices of industry professionals. Companies were requested to trial the domains to determine their relevance in practice and feedback was obtained. RESULTS Four PM-relevant domains were identified from the literature review: medical science and technology; translational and clinical application; governance and regulation and professional practice. Survey results refined these domains, and case studies within companies confirmed the potential for this framework to be used as an adjunct to current role specific competency frameworks to provide a specific focus on needed PM capabilities. CONCLUSION The framework was well accepted by local industry as a supplement to role specific competency frameworks to provide a structure on how to integrate new and evolving technologies into their current workforce development planning and build a continuous learning and cross-disciplinary mindset.
Collapse
Affiliation(s)
- Nicholette Conway
- GenomePlus Pty Ltd, Sydney, Australia
- Sydney Pharmacy School, Faculty of Medicine and Health, The University of Sydney, Sydney, NSW, 2006, Australia
| | - Orin Chisholm
- Sydney Pharmacy School, Faculty of Medicine and Health, The University of Sydney, Sydney, NSW, 2006, Australia.
| |
Collapse
|
3
|
Williams JJ, Tractenberg RE, Batut B, Becker EA, Brown AM, Burke ML, Busby B, Cooch NK, Dillman AA, Donovan SS, Doyle MA, van Gelder CWG, Hall CR, Hertweck KL, Jordan KL, Jungck JR, Latour AR, Lindvall JM, Lloret-Llinares M, McDowell GS, Morris R, Mourad T, Nisselle A, Ordóñez P, Paladin L, Palagi PM, Sukhai MA, Teal TK, Woodley L. An international consensus on effective, inclusive, and career-spanning short-format training in the life sciences and beyond. PLoS One 2023; 18:e0293879. [PMID: 37943810 PMCID: PMC10635508 DOI: 10.1371/journal.pone.0293879] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/14/2023] [Accepted: 10/23/2023] [Indexed: 11/12/2023] Open
Abstract
Science, technology, engineering, mathematics, and medicine (STEMM) fields change rapidly and are increasingly interdisciplinary. Commonly, STEMM practitioners use short-format training (SFT) such as workshops and short courses for upskilling and reskilling, but unaddressed challenges limit SFT's effectiveness and inclusiveness. Education researchers, students in SFT courses, and organizations have called for research and strategies that can strengthen SFT in terms of effectiveness, inclusiveness, and accessibility across multiple dimensions. This paper describes the project that resulted in a consensus set of 14 actionable recommendations to systematically strengthen SFT. A diverse international group of 30 experts in education, accessibility, and life sciences came together from 10 countries to develop recommendations that can help strengthen SFT globally. Participants, including representation from some of the largest life science training programs globally, assembled findings in the educational sciences and encompassed the experiences of several of the largest life science SFT programs. The 14 recommendations were derived through a Delphi method, where consensus was achieved in real time as the group completed a series of meetings and tasks designed to elicit specific recommendations. Recommendations cover the breadth of SFT contexts and stakeholder groups and include actions for instructors (e.g., make equity and inclusion an ethical obligation), programs (e.g., centralize infrastructure for assessment and evaluation), as well as organizations and funders (e.g., professionalize training SFT instructors; deploy SFT to counter inequity). Recommendations are aligned with a purpose-built framework-"The Bicycle Principles"-that prioritizes evidenced-based teaching, inclusiveness, and equity, as well as the ability to scale, share, and sustain SFT. We also describe how the Bicycle Principles and recommendations are consistent with educational change theories and can overcome systemic barriers to delivering consistently effective, inclusive, and career-spanning SFT.
Collapse
Affiliation(s)
- Jason J. Williams
- DNA Learning Center, Cold Spring Harbor Laboratory, Cold Spring Harbor, New York, United States of America
| | - Rochelle E. Tractenberg
- Collaborative for Research on Outcomes and Metrics, Georgetown University, Washington, DC, United States of America
| | - Bérénice Batut
- Albert-Ludwigs-University Freiburg, Freiburg, Germany
- Open Life Science, Freiburg, Germany
| | | | - Anne M. Brown
- Virginia Tech, Blacksburg, Virginia, United States of America
| | - Melissa L. Burke
- Australian BioCommons, North Melbourne, Australia
- Queensland Cyber Infrastructure Foundation, Research Computing Centre
- The University of Queensland
| | - Ben Busby
- DNAnexus, Mountain View, California, United States of America
| | | | | | | | | | | | - Christina R. Hall
- Australian BioCommons, North Melbourne, Australia
- University of Melbourne, Melbourne, Australia
| | - Kate L. Hertweck
- Chan Zuckerberg Initiative, Redwood City, California, United States of America
| | | | - John R. Jungck
- University of Delaware, Newark, DE, United States of America
| | | | | | - Marta Lloret-Llinares
- European Molecular Biology Laboratory, European Bioinformatics Institute, Cambridge, United Kingdom
| | - Gary S. McDowell
- Lightoller LLC
- The Ronin Institute, Montclair, NJ, United States of America
- Institute for Globally Distributed Open Research and Education
| | - Rana Morris
- National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health
| | - Teresa Mourad
- Ecological Society of America, Washington, DC, United States of America
| | - Amy Nisselle
- Murdoch Children’s Research Institute, Melbourne, Australia
- Melbourne Genomics, The University of Melbourne, Melbourne, Australia
| | - Patricia Ordóñez
- University of Maryland Baltimore County, Catonsville, Maryland, United States of America
| | - Lisanna Paladin
- European Molecular Biology Laboratory, Structural and Computational Biology Unit, Heidelberg, Germany
| | | | - Mahadeo A. Sukhai
- Canadian National Institute for the Blind, Toronto, Canada
- Queen’s University School of Medicine, Kingston, Canada
| | - Tracy K. Teal
- Posit, PBC, Boston, Massachusetts, United States of America
| | - Louise Woodley
- Center for Scientific Collaboration and Community Engagement, Oakland, California, United States of America
| |
Collapse
|
4
|
Piccolo SR, Denny P, Luxton-Reilly A, Payne SH, Ridge PG. Evaluating a large language model's ability to solve programming exercises from an introductory bioinformatics course. PLoS Comput Biol 2023; 19:e1011511. [PMID: 37769024 PMCID: PMC10564134 DOI: 10.1371/journal.pcbi.1011511] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2023] [Revised: 10/10/2023] [Accepted: 09/12/2023] [Indexed: 09/30/2023] Open
Abstract
Computer programming is a fundamental tool for life scientists, allowing them to carry out essential research tasks. However, despite various educational efforts, learning to write code can be a challenging endeavor for students and researchers in life-sciences disciplines. Recent advances in artificial intelligence have made it possible to translate human-language prompts to functional code, raising questions about whether these technologies can aid (or replace) life scientists' efforts to write code. Using 184 programming exercises from an introductory-bioinformatics course, we evaluated the extent to which one such tool-OpenAI's ChatGPT-could successfully complete programming tasks. ChatGPT solved 139 (75.5%) of the exercises on its first attempt. For the remaining exercises, we provided natural-language feedback to the model, prompting it to try different approaches. Within 7 or fewer attempts, ChatGPT solved 179 (97.3%) of the exercises. These findings have implications for life-sciences education and research. Instructors may need to adapt their pedagogical approaches and assessment techniques to account for these new capabilities that are available to the general public. For some programming tasks, researchers may be able to work in collaboration with machine-learning models to produce functional code.
Collapse
Affiliation(s)
- Stephen R. Piccolo
- Department of Biology, Brigham Young University, Provo, Utah, United States of America
| | - Paul Denny
- School of Computer Science, The University of Auckland, Auckland, New Zealand
| | | | - Samuel H. Payne
- Department of Biology, Brigham Young University, Provo, Utah, United States of America
| | - Perry G. Ridge
- Department of Biology, Brigham Young University, Provo, Utah, United States of America
| |
Collapse
|
5
|
Bartlett B, Stitt-Bergh M, Kantar M, Bingham JP. A data science practicum to introduce undergraduate students to bioinformatics for research. BIOCHEMISTRY AND MOLECULAR BIOLOGY EDUCATION : A BIMONTHLY PUBLICATION OF THE INTERNATIONAL UNION OF BIOCHEMISTRY AND MOLECULAR BIOLOGY 2023; 51:520-528. [PMID: 37401749 PMCID: PMC10621008 DOI: 10.1002/bmb.21762] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/21/2022] [Revised: 05/30/2023] [Accepted: 06/12/2023] [Indexed: 07/05/2023]
Abstract
An explosion of data available in the life sciences has shifted the discipline toward genomics and quantitative data science research. Institutions of higher learning have been addressing this shift by modifying undergraduate curriculums resulting in an increasing number of bioinformatics courses and research opportunities for undergraduates. The goal of this study was to explore how a newly designed introductory bioinformatics seminar could leverage the combination of in-class instruction and independent research to build the practical skill sets of undergraduate students beginning their careers in the life sciences. Participants were surveyed to assess learning perceptions toward the dual curriculum. Most students had a neutral or positive interest in these topics before the seminar and reported increased interest after the seminar. Students had increases in confidence level in their bioinformatic proficiency and understanding of ethical principles for data/genomic science. By combining undergraduate research with directed bioinformatics skills, classroom seminars facilitated a connection between student's life sciences knowledge and emerging research tools in computational biology.
Collapse
Affiliation(s)
- Bjarne Bartlett
- The University of Hawaii at Manoa, Department of Molecular Biosystems and Bioengineering, Honolulu, Hawaii, United States
| | - Monica Stitt-Bergh
- Assessment and Curriculum Support Center, The University of Hawaii at Manoa, Honolulu, Hawaii, United States
| | - Michael Kantar
- Department of Tropical Plant and Soil Sciences, The University of Hawaii at Manoa, Honolulu, Hawaii, United States
| | - Jon-Paul Bingham
- The University of Hawaii at Manoa, Department of Molecular Biosystems and Bioengineering, Honolulu, Hawaii, United States
| |
Collapse
|
6
|
Işık EB, Brazas MD, Schwartz R, Gaeta B, Palagi PM, van Gelder CWG, Suravajhala P, Singh H, Morgan SL, Zahroh H, Ling M, Satagopam VP, McGrath A, Nakai K, Tan TW, Gao G, Mulder N, Schönbach C, Zheng Y, De Las Rivas J, Khan AM. Grand challenges in bioinformatics education and training. Nat Biotechnol 2023; 41:1171-1174. [PMID: 37568018 DOI: 10.1038/s41587-023-01891-9] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 08/13/2023]
Affiliation(s)
- Esra Büşra Işık
- Beykoz Institute of Life Sciences and Biotechnology, Bezmialem Vakif University, Istanbul, Turkey
- APBioNET.org, Singapore, Singapore
| | - Michelle D Brazas
- Ontario Institute for Cancer Research, Toronto, Ontario, Canada
- Bioinformatics.ca, Toronto, Ontario, Canada
| | | | - Bruno Gaeta
- School of Computer Science and Engineering, University of New South Wales, Sydney, New South Wales, Australia
| | | | | | - Prashanth Suravajhala
- Amrita School of Biotechnology, Amrita Vishwa Vidyapeetham, Clappana, India
- Bioclues.org, Hyderabad, India
| | - Harpreet Singh
- APBioNET.org, Singapore, Singapore
- Bioclues.org, Hyderabad, India
- Department of Bioinformatics, Hans Raj Mahila Maha Vidyalaya, Jalandhar, India
| | - Sarah L Morgan
- European Molecular Biology Laboratory, European Bioinformatics Institute, Hinxton, UK
| | - Hilyatuz Zahroh
- APBioNET.org, Singapore, Singapore
- Genetics Research Centre, Universitas YARSI, Jakarta, Indonesia
| | - Maurice Ling
- APBioNET.org, Singapore, Singapore
- School of Applied Science, Temasek Polytechnic, Singapore, Singapore
| | - Venkata P Satagopam
- Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Belvaux, Luxembourg
- International Society for Computational Biology, Leesburg, VA, USA
| | | | - Kenta Nakai
- Institute of Medical Science, University of Tokyo, Tokyo, Japan
| | - Tin Wee Tan
- Department of Biochemistry, YLL School of Medicine, National University of Singapore, Singapore, Singapore
- National Supercomputing Centre, Singapore, Singapore
| | - Ge Gao
- State Key Laboratory of Protein and Plant Gene Research, School of Life Sciences, Biomedical Pioneering Innovative Center and Beijing Advanced Innovation Center for Genomics, Center for Bioinformatics, Peking University, Beijing, China
| | - Nicola Mulder
- Computational Biology Division, Department of Integrative Biomedical Sciences, University of Cape Town, Cape Town, South Africa
| | - Christian Schönbach
- Department of Biology, School of Sciences and Humanities, Nazarbayev University, Astana, Kazakhstan
| | - Yun Zheng
- School of Landscape and Horticulture, Yunnan Agricultural University, Kunming, China
| | - Javier De Las Rivas
- Cancer Research Center, Spanish National Research Council, University of Salamanca & Institute for Biomedical Research of Salamanca, Salamanca, Spain
| | - Asif M Khan
- Beykoz Institute of Life Sciences and Biotechnology, Bezmialem Vakif University, Istanbul, Turkey.
- APBioNET.org, Singapore, Singapore.
- Centre for Bioinformatics, School of Data Sciences, Perdana University, Kuala Lumpur, Malaysia.
- College of Computing and Information Technology, University of Doha for Science and Technology, Doha, Qatar.
| |
Collapse
|
7
|
Adenaike O, Olabanjo OE, Adedeji AA. Integrating computational skills in undergraduate Microbiology curricula in developing countries. Biol Methods Protoc 2023; 8:bpad008. [PMID: 37396465 PMCID: PMC10310463 DOI: 10.1093/biomethods/bpad008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2023] [Revised: 05/19/2023] [Accepted: 05/21/2023] [Indexed: 07/04/2023] Open
Abstract
The employability of young graduates has gained increasing significance in the labour market of the 21st century. Universities turn out millions of graduates annually, but at the same time, employers highlight their lack of the requisite skills for sustainable employment. We live today in a world of data, and therefore courses that feature numerical and computational tools to gather and analyse data are to be sourced for and integrated into life sciences' curricula as they provide a number of benefits for both the students and faculty members that are engaged in teaching the courses. The lack of this teaching in undergraduate Microbiology curricula is devastating and leaves a knowledge gap in the graduates that are turned out. This results in an inability of the emerging graduates to compete favourably with their counterparts from other parts of the world. There is a necessity on the part of life science educators to adapt their teaching strategies to best support students' curricula that prepare them for careers in science. Bioinformatics, Statistics and Programming are key computational skills to embrace by life scientists and the need for training beginning at undergraduate level cannot be overemphasized. This article reviews the need to integrate computational skills in undergraduate Microbiology curricula in developing countries with emphasis on Nigeria.
Collapse
Affiliation(s)
- Omolara Adenaike
- Correspondence address. Department of Biological Sciences (Microbiology Unit), Oduduwa University, Ipetumodu, Nigeria. Tel: +2348061278100; E-mail:
| | | | | |
Collapse
|
8
|
Castro LJ, Palagi PM, Beard N, Attwood TK, Brazas MD. Bioschemas training profiles: A set of specifications for standardizing training information to facilitate the discovery of training programs and resources. PLoS Comput Biol 2023; 19:e1011120. [PMID: 37319143 DOI: 10.1371/journal.pcbi.1011120] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/17/2023] Open
Abstract
Stand-alone life science training events and e-learning solutions are among the most sought-after modes of training because they address both point-of-need learning and the limited timeframes available for "upskilling." Yet, finding relevant life sciences training courses and materials is challenging because such resources are not marked up for internet searches in a consistent way. This absence of markup standards to facilitate discovery, re-use, and aggregation of training resources limits their usefulness and knowledge translation potential. Through a joint effort between the Global Organisation for Bioinformatics Learning, Education and Training (GOBLET), the Bioschemas Training community, and the ELIXIR FAIR Training Focus Group, a set of Bioschemas Training profiles has been developed, published, and implemented for life sciences training courses and materials. Here, we describe our development approach and methods, which were based on the Bioschemas model, and present the results for the 3 Bioschemas Training profiles: TrainingMaterial, Course, and CourseInstance. Several implementation challenges were encountered, which we discuss alongside potential solutions. Over time, continued implementation of these Bioschemas Training profiles by training providers will obviate the barriers to skill development, facilitating both the discovery of relevant training events to meet individuals' learning needs, and the discovery and re-use of training and instructional materials.
Collapse
Affiliation(s)
| | | | - Niall Beard
- Department of Computer Science, The University of Manchester, Manchester, United Kingdom
| | - Teresa K Attwood
- Department of Computer Science, The University of Manchester, Manchester, United Kingdom
| | | |
Collapse
|
9
|
Hargadon KM. A Bioinformatic Approach to Enhance Undergraduate Student Understanding of the Cancer-Immunity Cycle. JOURNAL OF CANCER EDUCATION : THE OFFICIAL JOURNAL OF THE AMERICAN ASSOCIATION FOR CANCER EDUCATION 2023; 38:991-999. [PMID: 36094725 PMCID: PMC9465667 DOI: 10.1007/s13187-022-02221-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Accepted: 08/27/2022] [Indexed: 06/02/2023]
Abstract
Recent advances in tumor immunology and cancer immunotherapy have generated significant interest in the field of immuno-oncology. With the promise of these advances comes an increasing need to train the next generation of scientists who will support ongoing basic and clinical research efforts in this field. At this time, however, there remains a documented underrepresentation of tumor immunology as a core content area in many undergraduate science curricula. This study introduces a novel pedagogical strategy that aimed to promote undergraduate student interest in tumor immunology in ways that support recent education guidelines published by the American Association of Immunologists, and it highlights the efficacy of this approach in enhancing student understanding of concepts relevant to the Cancer-Immunity Cycle. Using RNA-sequencing data obtained from clinical specimens catalogued in The Cancer Genome Atlas, students performed Kaplan-Meier survival analyses to identify Cancer-Immunity Cycle genes with prognostic significance. After correlating expression of such genes with tumor-infiltrating immune cell populations using a bioinformatic tool to deconvolute whole tumor-transcriptome data, students undertook an exercise that requires integration of course content and findings from the primary literature to generate hypotheses about the influence of genetic factors and immune cell types on the Cancer-Immunity Cycle and overall patient outcome. A pre-/post-project assessment instrument demonstrated the efficacy of this approach as a means of improving undergraduate student understanding of core cancer immunology concepts. This report describes these data and discusses potential ways in which the project can be adapted to extend its utility to broad and diverse student populations.
Collapse
Affiliation(s)
- Kristian M Hargadon
- Department of Biology, Hampden-Sydney College, Hampden-Sydney, VA, 23943, USA.
| |
Collapse
|
10
|
Karega P, Mwaura DK, Mwangi KW, Wanjiku M, Landi M, Kibet CK. Building awareness and capacity of bioinformatics and open science skills in Kenya: a sensitize, train, hack, and collaborate model. Front Res Metr Anal 2023; 8:1070390. [PMID: 37324282 PMCID: PMC10267827 DOI: 10.3389/frma.2023.1070390] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2022] [Accepted: 05/10/2023] [Indexed: 06/17/2023] Open
Abstract
We have applied the sensitize-train-hack-community model to build awareness of and capacity in bioinformatics in Kenya. Open science is the practice of science openly and collaboratively, with tools, techniques, and data freely shared to facilitate reuse and collaboration. Open science is not a mandatory curriculum course in schools, whereas bioinformatics is relatively new in some African regions. Open science tools can significantly enhance bioinformatics, leading to increased reproducibility. However, open science and bioinformatics skills, especially blended, are still lacking among students and researchers in resource-constrained regions. We note the need to be aware of the power of open science among the bioinformatics community and a clear strategy to learn bioinformatics and open science skills for use in research. Using the OpenScienceKE framework-Sensitize, Train, Hack, Collaborate/Community-the BOSS (Bioinformatics and Open Science Skills) virtual events built awareness and empowered researchers with the skills and tools in open science and bioinformatics. Sensitization was achieved through a symposium, training through a workshop and train-the-trainer program, hack through mini-projects, community through conferences, and continuous meet-ups. In this paper, we discuss how we applied the framework during the BOSS events and highlight lessons learnt in planning and executing the events and their impact on the outcome of each phase. We evaluate the impact of the events through anonymous surveys. We show that sensitizing and empowering researchers with the skills works best when the participants apply the skills to real-world problems: project-based learning. Furthermore, we have demonstrated how to implement virtual events in resource-constrained settings by providing Internet and equipment support to participants, thus improving accessibility and diversity.
Collapse
Affiliation(s)
- Pauline Karega
- International Center of Insect Physiology and Ecology, Nairobi, Kenya
- Department of Biochemistry, University of Nairobi, Nairobi, Kenya
| | | | | | - Margaret Wanjiku
- Department of Biology, San Diego State University, San Diego, CA, United States
| | - Michael Landi
- Department of Bioinformatics, Swedish University of Agricultural Sciences, Uppsala, Sweden
- International Institute of Tropical Agriculture, Nairobi, Kenya
| | - Caleb K. Kibet
- International Center of Insect Physiology and Ecology, Nairobi, Kenya
| |
Collapse
|
11
|
Parsania C, Chen R, Sethiya P, Miao Z, Dong L, Wong KH. FungiExpresZ: an intuitive package for fungal gene expression data analysis, visualization and discovery. Brief Bioinform 2023; 24:7043800. [PMID: 36806894 PMCID: PMC10025439 DOI: 10.1093/bib/bbad051] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/28/2022] [Revised: 01/13/2023] [Accepted: 01/26/2023] [Indexed: 02/22/2023] Open
Abstract
Bioinformatics analysis and visualization of high-throughput gene expression data require extensive computer programming skills, posing a bottleneck for many wet-lab scientists. In this work, we present an intuitive user-friendly platform for gene expression data analysis and visualization called FungiExpresZ. FungiExpresZ aims to help wet-lab scientists with little to no knowledge of computer programming to become self-reliant in bioinformatics analysis and generating publication-ready figures. The platform contains many commonly used data analysis tools and an extensive collection of pre-processed public ribonucleic acid sequencing (RNA-seq) datasets of many fungal species, including important human, plant and insect pathogens. Users may analyse their data alone or in combination with public RNA-seq data for an integrated analysis. The FungiExpresZ platform helps wet-lab scientists to overcome their limitations in genomics data analysis and can be applied to analyse data of any organism. FungiExpresZ is available as an online web-based tool (https://cparsania.shinyapps.io/FungiExpresZ/) and an offline R-Shiny package (https://github.com/cparsania/FungiExpresZ).
Collapse
Affiliation(s)
- Chirag Parsania
- Faculty of Health Sciences, University of Macau, Macau SAR of China
| | - Ruiwen Chen
- Faculty of Health Sciences, University of Macau, Macau SAR of China
| | - Pooja Sethiya
- Faculty of Health Sciences, University of Macau, Macau SAR of China
| | - Zhengqiang Miao
- Faculty of Health Sciences, University of Macau, Macau SAR of China
| | - Liguo Dong
- Faculty of Health Sciences, University of Macau, Macau SAR of China
| | - Koon Ho Wong
- Faculty of Health Sciences, University of Macau, Macau SAR of China
- Institute of Translational Medicine, University of Macau, Macau SAR of China
| |
Collapse
|
12
|
Gao L, Guo M. A course-based undergraduate research experience for bioinformatics education in undergraduate students. BIOCHEMISTRY AND MOLECULAR BIOLOGY EDUCATION : A BIMONTHLY PUBLICATION OF THE INTERNATIONAL UNION OF BIOCHEMISTRY AND MOLECULAR BIOLOGY 2023; 51:189-199. [PMID: 36779350 DOI: 10.1002/bmb.21710] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/02/2022] [Revised: 11/30/2022] [Accepted: 01/03/2023] [Indexed: 06/18/2023]
Abstract
With rapid development of sequencing technology and the continuous accumulation of biological big data, people who are capable of using bioinformatic skills to analyze omics data and work out biological problems are urgently needed in the workforce, which highlights the importance of developing bioinformatics skills early in the undergraduate curriculum. Meanwhile, course-based undergraduate research experience (CURE) courses have been proved to be an effective teaching format that have many advantages over traditional labs and lectures. Here we introduced an implementation of CURE course of bioinformatics data analysis and visualization for undergraduate students in major of bioinformatics and evaluated the learning outcomes. We were able to address 10 out of 15 core competencies identified by Network for Integrating Bioinformatics into Life Sciences Education. Besides, results evaluated by Laboratory Course Assessment Survey demonstrated the goals of collaboration, discovery and relevance, and iteration were accomplished in our course. Meanwhile, a significant increase in scores of final examinations and a long-term improvement on students' research ability on bioinformatics data analysis and visualization were also observed. In summary, this CURE course is useful for undergraduate students learning related knowledge and participate in authentic research in the field of bioinformatics.
Collapse
Affiliation(s)
- Lei Gao
- Department of Bioinformatics, School of Life Sciences, Shandong First Medical University & Shandong Academy of Medical Sciences, Tai'an, China
| | - Miao Guo
- Department of Biotechnology, School of Life Sciences, Shandong First Medical University & Shandong Academy of Medical Sciences, Tai'an, China
| |
Collapse
|
13
|
Savonen C, Wright C, Hoffman AM, Muschelli J, Cox K, Tan FJ, Leek JT. Open-source Tools for Training Resources - OTTR. JOURNAL OF STATISTICS AND DATA SCIENCE EDUCATION : AN OFFICIAL JOURNAL OF THE OF THE AMERICAN STATISTICAL ASSOCIATION 2023; 31:57-65. [PMID: 37207236 PMCID: PMC10193921 DOI: 10.1080/26939169.2022.2118646] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/21/2023]
Abstract
Data science and informatics tools are developing at a blistering rate, but their users often lack the educational background or resources to efficiently apply the methods to their research. Training resources and vignettes that accompany these tools often deprecate because their maintenance is not prioritized by funding, giving teams little time to devote to such endeavors. Our group has developed Open-source Tools for Training Resources (OTTR) to offer greater efficiency and flexibility for creating and maintaining these training resources. OTTR empowers creators to customize their work and allows for a simple workflow to publish using multiple platforms. OTTR allows content creators to publish training material to multiple massive online learner communities using familiar rendering mechanics. OTTR allows the incorporation of pedagogical practices like formative and summative assessments in the form of multiple choice questions and fill in the blank problems that are automatically graded. No local installation of any software is required to begin creating content with OTTR. Thus far, 15 training courses have been created with OTTR repository template. By using the OTTR system, the maintenance workload for updating these courses across platforms has been drastically reduced. For more information about OTTR and how to get started, go to ottrproject.org.
Collapse
Affiliation(s)
- Candace Savonen
- Johns Hopkins Bloomberg School of Public Health, Baltimore, MD
- Fred Hutchinson Cancer Center, Seattle, WA
- Corresponding author:
| | - Carrie Wright
- Johns Hopkins Bloomberg School of Public Health, Baltimore, MD
- Fred Hutchinson Cancer Center, Seattle, WA
| | - Ava M. Hoffman
- Johns Hopkins Bloomberg School of Public Health, Baltimore, MD
- Fred Hutchinson Cancer Center, Seattle, WA
| | - John Muschelli
- Johns Hopkins Bloomberg School of Public Health, Baltimore, MD
| | - Katherine Cox
- Johns Hopkins Bloomberg School of Public Health, Baltimore, MD
| | | | - Jeffrey T. Leek
- Johns Hopkins Bloomberg School of Public Health, Baltimore, MD
- Fred Hutchinson Cancer Center, Seattle, WA
| |
Collapse
|
14
|
Rasche H, Hyde C, Davis J, Gladman S, Coraor N, Bretaudeau A, Cuccuru G, Bacon W, Serrano-Solano B, Hillman-Jackson J, Hiltemann S, Zhou M, Grüning B, Stubbs A. Training Infrastructure as a Service. Gigascience 2022; 12:giad048. [PMID: 37395629 PMCID: PMC10316688 DOI: 10.1093/gigascience/giad048] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2023] [Revised: 05/31/2023] [Accepted: 06/08/2023] [Indexed: 07/04/2023] Open
Abstract
BACKGROUND Hands-on training, whether in bioinformatics or other domains, often requires significant technical resources and knowledge to set up and run. Instructors must have access to powerful compute infrastructure that can support resource-intensive jobs running efficiently. Often this is achieved using a private server where there is no contention for the queue. However, this places a significant prerequisite knowledge or labor barrier for instructors, who must spend time coordinating deployment and management of compute resources. Furthermore, with the increase of virtual and hybrid teaching, where learners are located in separate physical locations, it is difficult to track student progress as efficiently as during in-person courses. FINDINGS Originally developed by Galaxy Europe and the Gallantries project, together with the Galaxy community, we have created Training Infrastructure-as-a-Service (TIaaS), aimed at providing user-friendly training infrastructure to the global training community. TIaaS provides dedicated training resources for Galaxy-based courses and events. Event organizers register their course, after which trainees are transparently placed in a private queue on the compute infrastructure, which ensures jobs complete quickly, even when the main queue is experiencing high wait times. A built-in dashboard allows instructors to monitor student progress. CONCLUSIONS TIaaS provides a significant improvement for instructors and learners, as well as infrastructure administrators. The instructor dashboard makes remote events not only possible but also easy. Students experience continuity of learning, as all training happens on Galaxy, which they can continue to use after the event. In the past 60 months, 504 training events with over 24,000 learners have used this infrastructure for Galaxy training.
Collapse
Affiliation(s)
- Helena Rasche
- Department of Pathology and Clinical Bioinformatics, Erasmus Medical Center, Dr. Molewaterplein 40, 3015 GD, Rotterdam, the Netherlands
- School of Life Sciences and Technology, Avans University of Applied Sciences, Lovensdijkstraat 63, 4818 AJ Breda, the Netherlands
| | - Cameron Hyde
- Queensland Cyber Infrastructure Foundation Ltd., The University of Queensland, St. Lucia, QLD 4072, Australia
- University of the Sunshine Coast, Maroochydore, QLD 4558, Australia
| | - John Davis
- Department of Biology, Johns Hopkins University, Baltimore, MD 21218, USA
| | - Simon Gladman
- Melbourne Bioinformatics, The University of Melbourne, Melbourne, VIC 3051, Australia
| | - Nate Coraor
- School of Life, Health & Chemical Sciences, The Open University, Milton Keynes MK7 6AA, UK
| | - Anthony Bretaudeau
- IGEPP, INRAE, Institut Agro, University of Rennes, 35000 Rennes, France
- GenOuest Core Facility, University of Rennes, Inria, CNRS, IRISA, 35000 Rennes, France
| | - Gianmauro Cuccuru
- Bioinformatics Grou, Department of Computer Science, University of Freiburg, 79110 Freiburg im Breisgau, Germany
| | - Wendi Bacon
- School of Life, Health & Chemical Sciences, The Open University, Milton Keynes MK7 6AA, UK
| | - Beatriz Serrano-Solano
- Euro-Bioimaging ERIC Bio-Hub, EMBL, 69117 Heidelberg, Germany
- Department of Biochemistry and Molecular Biology, Eberly College of Science, The Pennsylvania State University, State College, PA 16802, USA
| | | | - Saskia Hiltemann
- Department of Pathology and Clinical Bioinformatics, Erasmus Medical Center, Dr. Molewaterplein 40, 3015 GD, Rotterdam, the Netherlands
| | - Miaomiao Zhou
- School of Life Sciences and Technology, Avans University of Applied Sciences, Lovensdijkstraat 63, 4818 AJ Breda, the Netherlands
| | - Björn Grüning
- Bioinformatics Grou, Department of Computer Science, University of Freiburg, 79110 Freiburg im Breisgau, Germany
| | - Andrew Stubbs
- Department of Pathology and Clinical Bioinformatics, Erasmus Medical Center, Dr. Molewaterplein 40, 3015 GD, Rotterdam, the Netherlands
| |
Collapse
|
15
|
Sun E, König SG, Cirstea M, Hallam SJ, Graves ML, Oliver DC. Development of a data science CURE in microbiology using publicly available microbiome datasets. Front Microbiol 2022; 13:1018237. [PMID: 36312919 PMCID: PMC9597637 DOI: 10.3389/fmicb.2022.1018237] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2022] [Accepted: 09/26/2022] [Indexed: 11/21/2022] Open
Abstract
Scientific and technological advances within the life sciences have enabled the generation of very large datasets that must be processed, stored, and managed computationally. Researchers increasingly require data science skills to work with these datasets at scale in order to convert information into actionable insights, and undergraduate educators have started to adapt pedagogies to fulfill this need. Course-based undergraduate research experiences (CUREs) have emerged as a leading model for providing large numbers of students with authentic research experiences including data science. Originally designed around wet-lab research experiences, CURE models have proliferated and diversified globally to accommodate a broad range of academic disciplines. Within microbiology, diversity metrics derived from microbiome sequence information have become standard data products in research. In some cases, researchers have deposited data in publicly accessible repositories, providing opportunities for reproducibility and comparative analysis. In 2020, with the onset of the COVID-19 pandemic and concomitant shift to remote learning, the University of British Columbia set out to develop an online data science CURE in microbiology. A team of faculty with collective domain expertise in microbiome research and CUREs developed and implemented a data science CURE in which teams of students learn to work with large publicly available datasets, develop and execute a novel scientific research project, and disseminate their findings in the online Undergraduate Journal of Experimental Microbiology and Immunology. Analysis of the resulting student-authored research articles, including comments from peer reviews conducted by subject matter experts, demonstrate high levels of learning effectiveness. Here, we describe core insights from course development and implementation based on a reverse course design model. Our approach to course design may be applicable to the development of other data science CUREs.
Collapse
Affiliation(s)
- Evelyn Sun
- Department of Microbiology and Immunology, University of British Columbia, Vancouver, BC, Canada
| | - Stephan G. König
- Department of Microbiology and Immunology, University of British Columbia, Vancouver, BC, Canada
| | - Mihai Cirstea
- Department of Microbiology and Immunology, University of British Columbia, Vancouver, BC, Canada
- Michael Smith Laboratories, University of British Columbia, Vancouver, BC, Canada
| | - Steven J. Hallam
- Department of Microbiology and Immunology, University of British Columbia, Vancouver, BC, Canada
- Graduate Program in Bioinformatics, University of British Columbia, Vancouver, BC, Canada
- Genome Science and Technology Program, University of British Columbia, Vancouver, BC, Canada
- Life Sciences Institute, University of British Columbia, Vancouver, BC, Canada
- ECOSCOPE Training Program, University of British Columbia, Vancouver, BC, Canada
| | - Marcia L. Graves
- Department of Microbiology and Immunology, University of British Columbia, Vancouver, BC, Canada
| | - David C. Oliver
- Department of Microbiology and Immunology, University of British Columbia, Vancouver, BC, Canada
- *Correspondence: David C. Oliver,
| |
Collapse
|
16
|
Ten simple rules for leveraging virtual interaction to build higher-level learning into bioinformatics short courses. PLoS Comput Biol 2022; 18:e1010220. [PMID: 35900972 PMCID: PMC9333319 DOI: 10.1371/journal.pcbi.1010220] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022] Open
|
17
|
Choudhary K, Pico AR. Introducing R as a smart version of calculators enables beginners to explore it on their own. F1000Res 2022; 10:859. [PMID: 35399224 PMCID: PMC8976183 DOI: 10.12688/f1000research.54685.2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 06/17/2022] [Indexed: 11/20/2022] Open
Abstract
Rapid technological advances in the past decades have enabled molecular biologists to generate large-scale and complex data with affordable resource investments, or obtain such data from public repositories. Yet, many graduate students, postdoctoral scholars, and senior researchers in the biosciences find themselves ill-equipped to analyze large-scale data. Global surveys have revealed that active researchers prefer short training workshops to fill their skill gaps. In this article, we focus on the challenge of delivering a short data analysis workshop to absolute beginners in computer programming. We propose that introducing R or other programming languages for data analysis as smart versions of calculators can help lower the communication barrier with absolute beginners. We describe this comparison with a few analogies and hope that other instructors will find them useful. We utilized these in our four-hour long training workshops involving participatory live coding, which we delivered in person and via videoconferencing. Anecdotal evidence suggests that our exposition made R programming seem easy and enabled beginners to explore it on their own.
Collapse
Affiliation(s)
- Krishna Choudhary
- Institute of Data Science and Biotechnology, Gladstone Institutes, San Francisco, CA, 94158, USA
- Diabetes Center, University of California San Francisco, San Francisco, CA, 94143, USA
| | - Alexander R. Pico
- Institute of Data Science and Biotechnology, Gladstone Institutes, San Francisco, CA, 94158, USA
| |
Collapse
|
18
|
Paiva VDA, Gomes IDS, Monteiro CR, Mendonça MV, Martins PM, Santana CA, Gonçalves-Almeida V, Izidoro SC, Melo-Minardi RCD, Silveira SDA. Protein structural bioinformatics: An overview. Comput Biol Med 2022; 147:105695. [DOI: 10.1016/j.compbiomed.2022.105695] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/19/2021] [Revised: 06/01/2022] [Accepted: 06/02/2022] [Indexed: 11/27/2022]
|
19
|
Garzón A, Rubio A, Pérez-Pulido AJ. E-learning strategies from a bioinformatics postgraduate programme to improve student engagement and completion rate. BIOINFORMATICS ADVANCES 2022; 2:vbac031. [PMID: 36699370 PMCID: PMC9710613 DOI: 10.1093/bioadv/vbac031] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 01/24/2022] [Revised: 04/16/2022] [Accepted: 04/29/2022] [Indexed: 01/28/2023]
Abstract
Motivation E-learning is the standard solution adopted in transnational study programmes for which multiple face-to-face learning places are not an option. Bioinformatics is compatible with e-learning because its resource requirements are low. Online learning, however, is usually associated with high dropout rates because students start from a very low computational level and/or they need support to conduct practical analyses on their own. Results In this article, we analyse the academic results of an online bioinformatics educational programme based on learning communities. The programme has been offered by the Spanish Pablo de Olavide University for more than 5 years with a completion rate of close to 90%. Learning bioinformatics requires technical and operational competencies that can only be acquired through a practical methodology. We have thus developed a student-centred and problem-based constructivist learning model; the model uses faculty and peer mentoring to drive individual work and retain students. Regarding our innovative learning model, the recruitment level (i.e. the number of applicants per available places and international origin), the results obtained (i.e. the retention index and learning outcomes) as well as the satisfaction index expressed by students and faculty lead us to regard this programme as a successful strategy for online graduate learning in bioinformatics. Availability and implementation All data and results for this article are available in the figures and supplementary files. The current syllabus (Supplementary File S7) and other details of the course are available at: https://www.upo.es/postgrado/Diploma-de-Especializacion-Analisis-Bioinformatico and https://www.upo.es/postgrado/Master-Analisis-Bioinformatico-Avanzado. Supplementary information Supplementary data are available at Bioinformatics Advances online.
Collapse
Affiliation(s)
- Andrés Garzón
- Andalusian Centre for Developmental Biology (CABD, UPO-CSIC-JA), Department of Molecular Biology and Biochemical Engineering, Faculty of Experimental Sciences, University Pablo de Olavide, Seville 41013, Spain
| | - Alejandro Rubio
- Andalusian Centre for Developmental Biology (CABD, UPO-CSIC-JA), Department of Molecular Biology and Biochemical Engineering, Faculty of Experimental Sciences, University Pablo de Olavide, Seville 41013, Spain
| | - Antonio J Pérez-Pulido
- Andalusian Centre for Developmental Biology (CABD, UPO-CSIC-JA), Department of Molecular Biology and Biochemical Engineering, Faculty of Experimental Sciences, University Pablo de Olavide, Seville 41013, Spain
| |
Collapse
|
20
|
Carland M, Pedersen H, Bose M, Novković B, Manson C, Lahan S, Pavlenko A, Yazdi PG, Grabherr MG. EZTraits: A programmable tool to evaluate multi-site deterministic traits. PLoS One 2022; 17:e0259327. [PMID: 35533190 PMCID: PMC9084532 DOI: 10.1371/journal.pone.0259327] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2021] [Accepted: 04/24/2022] [Indexed: 11/19/2022] Open
Abstract
The vast majority of human traits, including many disease phenotypes, are affected by alleles at numerous genomic loci. With a continually increasing set of variants with published clinical disease or biomarker associations, an easy-to-use tool for non-programmers to rapidly screen VCF files for risk alleles is needed. We have developed EZTraits as a tool to quickly evaluate genotype data against a set of rules defined by the user. These rules can be defined directly in the scripting language Lua, for genotype calls using variant ID (RS number) or chromosomal position. Alternatively, EZTraits can parse simple and intuitive text including concepts like ’any’ or ’all’. Thus, EZTraits is designed to support rapid genetic analysis and hypothesis-testing by researchers, regardless of programming experience or technical background. The software is implemented in C++ and compiles and runs on Linux and MacOS. The source code is available under the MIT license from https://github.com/selfdecode/rd-eztraits.
Collapse
Affiliation(s)
- Matt Carland
- SelfDecode.com, Miami, Florida, United States of America
| | - Haley Pedersen
- SelfDecode.com, Miami, Florida, United States of America
| | | | | | - Charles Manson
- SelfDecode.com, Miami, Florida, United States of America
| | - Shany Lahan
- SelfDecode.com, Miami, Florida, United States of America
| | - Alex Pavlenko
- SelfDecode.com, Miami, Florida, United States of America
| | - Puya G. Yazdi
- SelfDecode.com, Miami, Florida, United States of America
| | | |
Collapse
|
21
|
Bain SA, Plaisier H, Anderson F, Cook N, Crouch K, Meagher TR, Ritchie MG, Wallace EWJ, Barker D. Bringing bioinformatics to schools with the 4273pi project. PLoS Comput Biol 2022; 18:e1009705. [PMID: 35051174 PMCID: PMC8775354 DOI: 10.1371/journal.pcbi.1009705] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
Abstract
Over the last few decades, the nature of life sciences research has changed enormously, generating a need for a workforce with a variety of computational skills such as those required to store, manage, and analyse the large biological datasets produced by next-generation sequencing. Those with such expertise are increasingly in demand for employment in both research and industry. Despite this, bioinformatics education has failed to keep pace with advances in research. At secondary school level, computing is often taught in isolation from other sciences, and its importance in biological research is not fully realised, leaving pupils unprepared for the computational component of Higher Education and, subsequently, research in the life sciences. The 4273pi Bioinformatics at School project (https://4273pi.org) aims to address this issue by designing and delivering curriculum-linked, hands-on bioinformatics workshops for secondary school biology pupils, with an emphasis on equitable access. So far, we have reached over 180 schools across Scotland through visits or teacher events, and our open education resources are used internationally. Here, we describe our project, our aims and motivations, and the practical lessons we have learned from implementing a successful bioinformatics education project over the last 5 years.
Collapse
Affiliation(s)
- Stevie A. Bain
- Institute of Evolutionary Biology, School of Biological Sciences, University of Edinburgh, Edinburgh, United Kingdom
- * E-mail: (SAB); (HP); (DB)
| | - Heleen Plaisier
- Institute of Evolutionary Biology, School of Biological Sciences, University of Edinburgh, Edinburgh, United Kingdom
- * E-mail: (SAB); (HP); (DB)
| | - Felicity Anderson
- Institute for Cell Biology and SynthSys, School of Biological Sciences, University of Edinburgh, Edinburgh, United Kingdom
| | - Nicola Cook
- Centre for Biological Diversity, School of Biology, University of St Andrews, St Andrews, United Kingdom
| | - Kathryn Crouch
- Wellcome Centre for Integrative Parasitology, University of Glasgow, Glasgow, United Kingdom
| | - Thomas R. Meagher
- Centre for Biological Diversity, School of Biology, University of St Andrews, St Andrews, United Kingdom
| | - Michael G. Ritchie
- Centre for Biological Diversity, School of Biology, University of St Andrews, St Andrews, United Kingdom
| | - Edward W. J. Wallace
- Institute for Cell Biology and SynthSys, School of Biological Sciences, University of Edinburgh, Edinburgh, United Kingdom
| | - Daniel Barker
- Institute of Evolutionary Biology, School of Biological Sciences, University of Edinburgh, Edinburgh, United Kingdom
- * E-mail: (SAB); (HP); (DB)
| |
Collapse
|
22
|
Noor A. Improving bioinformatics software quality through incorporation of software engineering practices. PeerJ Comput Sci 2022; 8:e839. [PMID: 35111923 PMCID: PMC8771759 DOI: 10.7717/peerj-cs.839] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2021] [Accepted: 12/13/2021] [Indexed: 06/14/2023]
Abstract
BACKGROUND Bioinformatics software is developed for collecting, analyzing, integrating, and interpreting life science datasets that are often enormous. Bioinformatics engineers often lack the software engineering skills necessary for developing robust, maintainable, reusable software. This study presents review and discussion of the findings and efforts made to improve the quality of bioinformatics software. METHODOLOGY A systematic review was conducted of related literature that identifies core software engineering concepts for improving bioinformatics software development: requirements gathering, documentation, testing, and integration. The findings are presented with the aim of illuminating trends within the research that could lead to viable solutions to the struggles faced by bioinformatics engineers when developing scientific software. RESULTS The findings suggest that bioinformatics engineers could significantly benefit from the incorporation of software engineering principles into their development efforts. This leads to suggestion of both cultural changes within bioinformatics research communities as well as adoption of software engineering disciplines into the formal education of bioinformatics engineers. Open management of scientific bioinformatics development projects can result in improved software quality through collaboration amongst both bioinformatics engineers and software engineers. CONCLUSIONS While strides have been made both in identification and solution of issues of particular import to bioinformatics software development, there is still room for improvement in terms of shifts in both the formal education of bioinformatics engineers as well as the culture and approaches of managing scientific bioinformatics research and development efforts.
Collapse
|
23
|
Data science in undergraduate medicine: Course overview and student perspectives. Int J Med Inform 2021; 159:104668. [PMID: 35033982 DOI: 10.1016/j.ijmedinf.2021.104668] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2021] [Revised: 12/14/2021] [Accepted: 12/15/2021] [Indexed: 11/23/2022]
Abstract
BACKGROUND Despite the growing interest in health data science education, it is not embedded in undergraduate medical curricula and little is known about best teaching practices. This paper presents a highly innovative course in a UK university that introduces undergraduate medical students to data science. It also discusses a study on student perspectives on the learning and teaching of health data science. METHODS The pedagogical design elements of the Data Science in Medicine course are discussed, along with its syllabus, assessment methodology and flipped classroom delivery. The course has been offered to approximately 630 students over three years. Student perspectives were investigated through three focus groups with the participation of 19 students across different study years in medicine. An experiment was conducted regarding instructor-led vs. video-based modalities of online programming labs, with the participation of 8 students. RESULTS The course has led to improved data competency among medical students and to a positive change in their opinions about data science. Motivating the course and showing relevance to clinical practice was one of the biggest challenges. Statistics was perceived by focus group participants as an essential data skill. Including data science in the medical curriculum was perceived as important by Year 1 students, while opinions varied between Year 4/5 participants. Video-based online labs were preferred over instructor-led online labs, and they were found to be more useful and enjoyable, without leading to any significant difference in academic performance. CONCLUSIONS Teaching data science to undergraduate medicine students is highly desirable and feasible. We recommend including statistics in the curriculum and practical skill development through simple and clinically-relevant data science tasks, supported through video-based online labs. Further reporting on similar courses is needed, as well as larger-scale studies on student perspectives.
Collapse
|
24
|
Engel H, Guischard F, Krause F, Nandy J, Kaas P, Höfflin N, Köhn M, Kilb N, Voigt K, Wolf S, Aslan T, Baezner F, Hahne S, Ruckes C, Weygant J, Zinina A, Akmeriç EB, Antwi EB, Dombrovskij D, Franke P, Lesch KL, Vesper N, Weis D, Gensch N, Di Ventura B, Öztürk MA. finDr: A web server for in silico D-peptide ligand identification. Synth Syst Biotechnol 2021; 6:402-413. [PMID: 34901479 PMCID: PMC8632724 DOI: 10.1016/j.synbio.2021.11.004] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2021] [Revised: 09/20/2021] [Accepted: 11/08/2021] [Indexed: 11/18/2022] Open
Abstract
In the rapidly expanding field of peptide therapeutics, the short in vivo half-life of peptides represents a considerable limitation for drug action. D-peptides, consisting entirely of the dextrorotatory enantiomers of naturally occurring levorotatory amino acids (AAs), do not suffer from these shortcomings as they are intrinsically resistant to proteolytic degradation, resulting in a favourable pharmacokinetic profile. To experimentally identify D-peptide binders to interesting therapeutic targets, so-called mirror-image phage display is typically performed, whereby the target is synthesized in D-form and L-peptide binders are screened as in conventional phage display. This technique is extremely powerful, but it requires the synthesis of the target in D-form, which is challenging for large proteins. Here we present finDr, a novel web server for the computational identification and optimization of D-peptide ligands to any protein structure (https://findr.biologie.uni-freiburg.de/). finDr performs molecular docking to virtually screen a library of helical 12-mer peptides extracted from the RCSB Protein Data Bank (PDB) for their ability to bind to the target. In a separate, heuristic approach to search the chemical space of 12-mer peptides, finDr executes a customizable evolutionary algorithm (EA) for the de novo identification or optimization of D-peptide ligands. As a proof of principle, we demonstrate the validity of our approach to predict optimal binders to the pharmacologically relevant target phenol soluble modulin alpha 3 (PSMα3), a toxin of methicillin-resistant Staphylococcus aureus (MRSA). We validate the predictions using in vitro binding assays, supporting the success of this approach. Compared to conventional methods, finDr provides a low cost and easy-to-use alternative for the identification of D-peptide ligands against protein targets of choice without size limitation. We believe finDr will facilitate D-peptide discovery with implications in biotechnology and biomedicine.
Collapse
Key Words
- D-AA, dextrorotatory amino acid
- D-peptide
- EA, evolutionary algorithm
- Evolutionary algorithm
- L-AA, levorotatory amino acid
- MD, molecular dynamics
- MIEA, mirror-image evolutionary algorithm
- MIPD, mirror-image phage display
- MIVS, mirror-image virtual screening
- MRSA, methicillin-resistant Staphylococcus aureus
- Mirror-image phage display
- Molecular docking
- NCL, native chemical ligation
- PD-1, receptor programmed death 1
- PPI, protein-protein interaction
- PSMα3, phenol soluble modulin alpha 3
- Peptide design
- SPPS, solid phase peptide synthesis
- Web server
Collapse
Affiliation(s)
- Helena Engel
- Signalling Research Centres BIOSS and CIBSS, University of Freiburg, Schänzlestr. 18, 79104, Freiburg, Germany
| | - Felix Guischard
- Signalling Research Centres BIOSS and CIBSS, University of Freiburg, Schänzlestr. 18, 79104, Freiburg, Germany
| | - Fabian Krause
- Signalling Research Centres BIOSS and CIBSS, University of Freiburg, Schänzlestr. 18, 79104, Freiburg, Germany
| | - Janina Nandy
- Signalling Research Centres BIOSS and CIBSS, University of Freiburg, Schänzlestr. 18, 79104, Freiburg, Germany
| | - Paulina Kaas
- Signalling Research Centres BIOSS and CIBSS, University of Freiburg, Schänzlestr. 18, 79104, Freiburg, Germany
| | - Nico Höfflin
- Signalling Research Centres BIOSS and CIBSS, University of Freiburg, Schänzlestr. 18, 79104, Freiburg, Germany
- Institute of Biology III, Faculty of Biology, University of Freiburg, Schänzlestr. 1, 79104, Freiburg, Germany
| | - Maja Köhn
- Signalling Research Centres BIOSS and CIBSS, University of Freiburg, Schänzlestr. 18, 79104, Freiburg, Germany
- Institute of Biology III, Faculty of Biology, University of Freiburg, Schänzlestr. 1, 79104, Freiburg, Germany
| | - Normann Kilb
- Institute of Biology II, Faculty of Biology, University of Freiburg, Schänzlestr. 1, 79104, Freiburg, Germany
- AG Roth-Lab for MicroarrayCopying, ZBSA–Centre for Biological Systems Analysis, University of Freiburg, Habsburgerstrasse 49, 79104, Freiburg, Germany
| | - Karsten Voigt
- Institute of Biology III, Faculty of Biology, University of Freiburg, Schänzlestr. 1, 79104, Freiburg, Germany
| | - Steffen Wolf
- Biomolecular Dynamics, Institute of Physics, University of Freiburg, Hermann-Herder-Strasse 3a, 79104, Freiburg, Germany
| | - Tahira Aslan
- Signalling Research Centres BIOSS and CIBSS, University of Freiburg, Schänzlestr. 18, 79104, Freiburg, Germany
| | - Fabian Baezner
- Signalling Research Centres BIOSS and CIBSS, University of Freiburg, Schänzlestr. 18, 79104, Freiburg, Germany
| | - Salomé Hahne
- Signalling Research Centres BIOSS and CIBSS, University of Freiburg, Schänzlestr. 18, 79104, Freiburg, Germany
| | - Carolin Ruckes
- Signalling Research Centres BIOSS and CIBSS, University of Freiburg, Schänzlestr. 18, 79104, Freiburg, Germany
| | - Joshua Weygant
- Signalling Research Centres BIOSS and CIBSS, University of Freiburg, Schänzlestr. 18, 79104, Freiburg, Germany
| | - Alisa Zinina
- Signalling Research Centres BIOSS and CIBSS, University of Freiburg, Schänzlestr. 18, 79104, Freiburg, Germany
| | - Emir Bora Akmeriç
- Signalling Research Centres BIOSS and CIBSS, University of Freiburg, Schänzlestr. 18, 79104, Freiburg, Germany
| | - Enoch B. Antwi
- Signalling Research Centres BIOSS and CIBSS, University of Freiburg, Schänzlestr. 18, 79104, Freiburg, Germany
| | - Dennis Dombrovskij
- Signalling Research Centres BIOSS and CIBSS, University of Freiburg, Schänzlestr. 18, 79104, Freiburg, Germany
| | - Philipp Franke
- Institute for Biochemistry, University of Freiburg, Albertstr. 21, 79104, Freiburg, Germany
| | - Klara L. Lesch
- Signalling Research Centres BIOSS and CIBSS, University of Freiburg, Schänzlestr. 18, 79104, Freiburg, Germany
- Institute of Biology II, Faculty of Biology, University of Freiburg, Schänzlestr. 1, 79104, Freiburg, Germany
- Spemann Graduate School of Biology and Medicine (SGBM), University of Freiburg, Albertstraße 19A, 79104, Freiburg, Germany
- Internal Medicine IV, Department of Medicine, Medical Center, University of Freiburg, Hugstetter Straße 55, 79106, Freiburg, Germany
| | - Niklas Vesper
- Signalling Research Centres BIOSS and CIBSS, University of Freiburg, Schänzlestr. 18, 79104, Freiburg, Germany
| | - Daniel Weis
- Signalling Research Centres BIOSS and CIBSS, University of Freiburg, Schänzlestr. 18, 79104, Freiburg, Germany
| | - Nicole Gensch
- Core Facility Signalling Factory, Centre for Biological Signaling Studies (BIOSS), University of Freiburg, Schänzlestr. 18, 79104, Freiburg, Germany
- Corresponding author. Core Facility Signalling Factory, Centre for Biological Signaling Studies (BIOSS), University of Freiburg, Schänzlestr. 18, 79104, Freiburg, Germany.
| | - Barbara Di Ventura
- Signalling Research Centres BIOSS and CIBSS, University of Freiburg, Schänzlestr. 18, 79104, Freiburg, Germany
- Institute of Biology II, Faculty of Biology, University of Freiburg, Schänzlestr. 1, 79104, Freiburg, Germany
- Corresponding author. Signalling Research Centres BIOSS and CIBSS, University of Freiburg, Schänzlestr. 18, 79104, Freiburg, Germany.
| | - Mehmet Ali Öztürk
- Signalling Research Centres BIOSS and CIBSS, University of Freiburg, Schänzlestr. 18, 79104, Freiburg, Germany
- Institute of Biology II, Faculty of Biology, University of Freiburg, Schänzlestr. 1, 79104, Freiburg, Germany
- Corresponding author. Signalling Research Centres BIOSS and CIBSS, University of Freiburg, Schänzlestr. 18, 79104, Freiburg, Germany.
| |
Collapse
|
25
|
Cao M, Li L, Xu L, Fang M, Xing X, Zhou C, Ren W, Wang L, Jing F. STAT1: a novel candidate biomarker and potential therapeutic target of the recurrent aphthous stomatitis. BMC Oral Health 2021; 21:524. [PMID: 34649540 PMCID: PMC8515754 DOI: 10.1186/s12903-021-01776-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2021] [Accepted: 07/13/2021] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND The recurrent aphthous stomatitis (RAS) frequently affects patient quality of life as a result of long lasting and recurrent episodes of burning pain. However, there were temporarily few available effective medical therapies currently. Drug target identification was the first step in drug discovery, was usually finding the best interaction mode between the potential target candidates and probe small molecules. Therefore, elucidating the molecular mechanism of RAS pathogenesis and exploring the potential molecular targets of medical therapies for RAS was of vital importance. METHODS Bioinformatics data mining techniques were applied to explore potential novel targets, weighted gene co-expression network analysis (WGCNA) was used to construct a co-expression module of the gene chip data from GSE37265, and the hub genes were identified by the Molecular Complex Detection (MCODE) plugin. RESULTS A total of 16 co-expression modules were identified, and 30 hub genes in the turquoise module were identified. In addition, functional analysis of Hub genes in modules of interest was performed, which indicated that such hub genes were mainly involved in pathways related to immune response, virus infection, epithelial cell, signal transduction. Two clusters (highly interconnected regions) were determined in the network, with score = 17.647 and 10, respectively, cluster 1 and cluster 2 are linked by STAT1 and ICAM1, it is speculated that STAT1 may be a primary gene of RAS. Finally, genistein, daidzein, kaempferol, resveratrol, rosmarinic acid, triptolide, quercetin and (-)-epigallocatechin-3-gallate were selected from the TCMSP database, and both of them is the STAT-1 inhibitor. The results of reverse molecular docking suggest that in addition to triptolide, (-)-Epigallocatechin-3-gallate and resveratrol, the other 5 compounds (flavonoids) with similar structures may bind to the same position of STAT1 protein with different docking score. CONCLUSIONS Our study identified STAT1 as the potential biomarkers that might contribute to the diagnosis and potential therapeutic target of RAS, and we can also screen RAS therapeutic drugs from STAT-1 inhibitors.
Collapse
Affiliation(s)
- Mingchen Cao
- Department of Pharmacy, The Affiliated Hospital of Qingdao University, Qingdao, China
| | - Lei Li
- Department of Pharmacy, The Affiliated Hospital of Qingdao University, Qingdao, China
| | - Long Xu
- Department of Pharmacy, The Affiliated Hospital of Qingdao University, Qingdao, China
| | - Mengxiang Fang
- Department of Pharmacy, Huang Dao District Second Hospital of Traditional Chinese Medicine, Qingdao, China
| | - Xiaomin Xing
- Department of Pharmacy, The Affiliated Hospital of Qingdao University, Qingdao, China
| | - Changkai Zhou
- Department of Pharmacy, The Affiliated Hospital of Qingdao University, Qingdao, China
| | - Wei Ren
- Department of Pharmacy, The Affiliated Hospital of Qingdao University, Qingdao, China
| | - Longyuan Wang
- Department of Pharmacy, The Affiliated Hospital of Qingdao University, Qingdao, China
| | - Fanbo Jing
- Department of Pharmacy, The Affiliated Hospital of Qingdao University, Qingdao, China.
| |
Collapse
|
26
|
Blanco E, González-Ramírez M, Di Croce L. Productive visualization of high-throughput sequencing data using the SeqCode open portable platform. Sci Rep 2021; 11:19545. [PMID: 34599234 PMCID: PMC8486768 DOI: 10.1038/s41598-021-98889-7] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2021] [Accepted: 08/20/2021] [Indexed: 12/23/2022] Open
Abstract
Large-scale sequencing techniques to chart genomes are entirely consolidated. Stable computational methods to perform primary tasks such as quality control, read mapping, peak calling, and counting are likewise available. However, there is a lack of uniform standards for graphical data mining, which is also of central importance. To fill this gap, we developed SeqCode, an open suite of applications that analyzes sequencing data in an elegant but efficient manner. Our software is a portable resource written in ANSI C that can be expected to work for almost all genomes in any computational configuration. Furthermore, we offer a user-friendly front-end web server that integrates SeqCode functions with other graphical analysis tools. Our analysis and visualization toolkit represents a significant improvement in terms of performance and usability as compare to other existing programs. Thus, SeqCode has the potential to become a key multipurpose instrument for high-throughput professional analysis; further, it provides an extremely useful open educational platform for the world-wide scientific community. SeqCode website is hosted at http://ldicrocelab.crg.eu, and the source code is freely distributed at https://github.com/eblancoga/seqcode.
Collapse
Affiliation(s)
- Enrique Blanco
- Centre for Genomic Regulation (CRG), Barcelona Institute for Science and Technology (BIST), Dr. Aiguader 88, 08003, Barcelona, Spain.
| | - Mar González-Ramírez
- Centre for Genomic Regulation (CRG), Barcelona Institute for Science and Technology (BIST), Dr. Aiguader 88, 08003, Barcelona, Spain
| | - Luciano Di Croce
- Centre for Genomic Regulation (CRG), Barcelona Institute for Science and Technology (BIST), Dr. Aiguader 88, 08003, Barcelona, Spain. .,Universitat Pompeu Fabra (UPF), Barcelona, Spain. .,ICREA, Passeig Lluis Companys 23, 08010, Barcelona, Spain.
| |
Collapse
|
27
|
Yang L, Zheng S, Xu X, Sun Y, Wang X, Li J. Medical Data Mining Course Development in Postgraduate Medical Education: Web-Based Survey and Case Study. JMIR MEDICAL EDUCATION 2021; 7:e24027. [PMID: 34596575 PMCID: PMC8520135 DOI: 10.2196/24027] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 09/01/2020] [Revised: 11/16/2020] [Accepted: 08/08/2021] [Indexed: 06/13/2023]
Abstract
BACKGROUND Medical postgraduates' demand for data capabilities is growing, as biomedical research becomes more data driven, integrative, and computational. In the context of the application of big data in health and medicine, the integration of data mining skills into postgraduate medical education becomes important. OBJECTIVE This study aimed to demonstrate the design and implementation of a medical data mining course for medical postgraduates with diverse backgrounds in a medical school. METHODS We developed a medical data mining course called "Practical Techniques of Medical Data Mining" for postgraduate medical education and taught the course online at Peking Union Medical College (PUMC). To identify the background knowledge, programming skills, and expectations of targeted learners, we conducted a web-based questionnaire survey. After determining the instructional methods to be used in the course, three technical platforms-Rain Classroom, Tencent Meeting, and WeChat-were chosen for online teaching. A medical data mining platform called Medical Data Mining - R Programming Hub (MedHub) was developed for self-learning, which could support the development and comprehensive testing of data mining algorithms. Finally, we carried out a postcourse survey and a case study to demonstrate that our online course could accommodate a diverse group of medical students with a wide range of academic backgrounds and programming experience. RESULTS In total, 200 postgraduates from 30 disciplines participated in the precourse survey. Based on the analysis of students' characteristics and expectations, we designed an optimized course structured into nine logical teaching units (one 4-hour unit per week for 9 weeks). The course covered basic knowledge of R programming, machine learning models, clinical data mining, and omics data mining, among other topics, as well as diversified health care analysis scenarios. Finally, this 9-week course was successfully implemented in an online format from May to July in the spring semester of 2020 at PUMC. A total of 6 faculty members and 317 students participated in the course. Postcourse survey data showed that our course was considered to be very practical (83/83, 100% indicated "very positive" or "positive"), and MedHub received the best feedback, both in function (80/83, 96% chose "satisfied") and teaching effect (80/83, 96% chose "satisfied"). The case study showed that our course was able to fill the gap between student expectations and learning outcomes. CONCLUSIONS We developed content for a data mining course, with online instructional methods to accommodate the diversified characteristics of students. Our optimized course could improve the data mining skills of medical students with a wide range of academic backgrounds and programming experience.
Collapse
Affiliation(s)
- Lin Yang
- Institute of Medical Information and Library, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Si Zheng
- Institute of Medical Information and Library, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Xiaowei Xu
- Institute of Medical Information and Library, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Yueping Sun
- Institute of Medical Information and Library, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Xuwen Wang
- Institute of Medical Information and Library, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| | - Jiao Li
- Institute of Medical Information and Library, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
| |
Collapse
|
28
|
Jjingo D, Mboowa G, Sserwadda I, Kakaire R, Kiberu D, Amujal M, Galiwango R, Kateete D, Joloba M, Whalen CC. Bioinformatics mentorship in a resource limited setting. Brief Bioinform 2021; 23:6377513. [PMID: 34591953 PMCID: PMC8769693 DOI: 10.1093/bib/bbab399] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2021] [Revised: 08/11/2021] [Accepted: 09/01/2021] [Indexed: 12/27/2022] Open
Abstract
BACKGROUND The two recent simultaneous developments of high-throughput sequencing and increased computational power have brought bioinformatics to the forefront as an important tool for effective and efficient biomedical research. Consequently, there have been multiple approaches to developing bioinformatics skills. In resource rich environments, it has been possible to develop and implement formal fully accredited graduate degree training programs in bioinformatics. In resource limited settings with a paucity of expert bioinformaticians, infrastructure and financial resources, the task has been approached by delivering short courses on bioinformatics-lasting only a few days to a couple of weeks. Alternatively, courses are offered online, usually over a period of a few months. These approaches are limited by both the lack of sustained in-person trainer-trainee interactions, which is a key part of quality mentorships and short durations which constrain the amount of learning that can be achieved. METHODS Here, we pioneered and tested a bioinformatics training/mentorship model that effectively uses the available expertise and computational infrastructure to deliver an in-person hands-on skills training experience. This is done through a few physical lecture hours each week, guided personal coursework over the rest of the week, group discussions and continuous close mentorship and assessment of trainees over a period of 1 year. RESULTS This model has now completed its third iteration at Makerere University and has successfully mentored trainees, who have progressed to a variety of viable career paths. CONCLUSIONS One-year (intermediate) skills based in-person bioinformatics training and mentorships are viable, effective and particularly appropriate for resource limited settings.
Collapse
Affiliation(s)
- Daudi Jjingo
- The African Center of Excellence in Bioinformatics and Data Intensive Sciences, the Infectious Diseases Institute, Makerere University, Kampala-Uganda.,Department of Computer Science, College of Computing and Information Sciences, Makerere University, Kampala-Uganda
| | - Gerald Mboowa
- The African Center of Excellence in Bioinformatics and Data Intensive Sciences, the Infectious Diseases Institute, Makerere University, Kampala-Uganda.,Department of Immunology and Molecular Biology, College of Health Sciences, Makerere University, Kampala-Uganda
| | - Ivan Sserwadda
- The African Center of Excellence in Bioinformatics and Data Intensive Sciences, the Infectious Diseases Institute, Makerere University, Kampala-Uganda.,Department of Immunology and Molecular Biology, College of Health Sciences, Makerere University, Kampala-Uganda
| | - Robert Kakaire
- Department of Epidemiology and Biostatistics, College of Public Health, University of Georgia, Athens, GA, USA
| | - Davis Kiberu
- The African Center of Excellence in Bioinformatics and Data Intensive Sciences, the Infectious Diseases Institute, Makerere University, Kampala-Uganda
| | - Marion Amujal
- Department of Immunology and Molecular Biology, College of Health Sciences, Makerere University, Kampala-Uganda
| | - Ronald Galiwango
- The African Center of Excellence in Bioinformatics and Data Intensive Sciences, the Infectious Diseases Institute, Makerere University, Kampala-Uganda.,Department of Immunology and Molecular Biology, College of Health Sciences, Makerere University, Kampala-Uganda
| | - David Kateete
- Department of Immunology and Molecular Biology, College of Health Sciences, Makerere University, Kampala-Uganda.,Department of Medical Microbiology, College of Health Sciences, Makerere University, Kampala-Uganda
| | - Moses Joloba
- Department of Immunology and Molecular Biology, College of Health Sciences, Makerere University, Kampala-Uganda.,Department of Medical Microbiology, College of Health Sciences, Makerere University, Kampala-Uganda
| | - Christopher C Whalen
- Department of Epidemiology and Biostatistics, College of Public Health, University of Georgia, Athens, GA, USA
| |
Collapse
|
29
|
Community development, implementation, and assessment of a NIBLSE bioinformatics sequence similarity learning resource. PLoS One 2021; 16:e0257404. [PMID: 34506617 PMCID: PMC8432852 DOI: 10.1371/journal.pone.0257404] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2021] [Accepted: 08/31/2021] [Indexed: 11/19/2022] Open
Abstract
As powerful computational tools and 'big data' transform the biological sciences, bioinformatics training is becoming necessary to prepare the next generation of life scientists. Furthermore, because the tools and resources employed in bioinformatics are constantly evolving, bioinformatics learning materials must be continuously improved. In addition, these learning materials need to move beyond today's typical step-by-step guides to promote deeper conceptual understanding by students. One of the goals of the Network for Integrating Bioinformatics into Life Sciences Education (NIBSLE) is to create, curate, disseminate, and assess appropriate open-access bioinformatics learning resources. Here we describe the evolution, integration, and assessment of a learning resource that explores essential concepts of biological sequence similarity. Pre/post student assessment data from diverse life science courses show significant learning gains. These results indicate that the learning resource is a beneficial educational product for the integration of bioinformatics across curricula.
Collapse
|
30
|
Taylor MD, Mendenhall B, Woods CS, Rasband ME, Vallejo MC, Bailey EG, Payne SH. Online Tools for Teaching Cancer Bioinformatics. JOURNAL OF MICROBIOLOGY & BIOLOGY EDUCATION 2021; 22:jmbe00167-21. [PMID: 34594439 PMCID: PMC8442005 DOI: 10.1128/jmbe.00167-21] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/24/2021] [Accepted: 07/19/2021] [Indexed: 06/02/2023]
Abstract
The rise of deep molecular characterization with omics data as a standard in biological sciences has highlighted a need for expanded instruction in bioinformatics curricula. Many large biology data sets are publicly available and offer an incredible opportunity for educators to help students explore biological phenomena with computational tools, including data manipulation, visualization, and statistical assessment. However, logistical barriers to data access and integration often complicate their use in undergraduate education. Here, we present a cancer bioinformatics module that is designed to overcome these barriers through six exercises containing authentic, biologically motivated computational exercises that demonstrate how modern omics data are used in precision oncology. Upper-division undergraduate students develop advanced Python programming and data analysis skills with real-world oncology data which integrates proteomics and genomics. The module is publicly available and open source at https://paynelab.github.io/biograder/bio462. These hands-on activities include explanatory text, code demonstrations, and practice problems and are ready to implement in bioinformatics courses.
Collapse
Affiliation(s)
- Mason D. Taylor
- Department of Biology, Brigham Young University, Provo, Utah, USA
| | - Bryn Mendenhall
- Department of Biology, Brigham Young University, Provo, Utah, USA
| | - Calvin S. Woods
- Department of Biology, Brigham Young University, Provo, Utah, USA
| | | | | | | | - Samuel H. Payne
- Department of Biology, Brigham Young University, Provo, Utah, USA
| |
Collapse
|
31
|
Ahmed AE, Awadallah AA, Tagelsir M, Suliman MA, Eltigani A, Elsafi H, Hamdelnile BD, Mukhtar MA, Fadlelmola FM. Delivering blended bioinformatics training in resource-limited settings: a case study on the University of Khartoum H3ABioNet node. Brief Bioinform 2021; 21:719-728. [PMID: 30773584 PMCID: PMC7299290 DOI: 10.1093/bib/bbz004] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/07/2018] [Revised: 12/12/2018] [Accepted: 01/01/2019] [Indexed: 11/16/2022] Open
Abstract
Motivation Delivering high-quality distance-based courses in resource-limited settings is a challenging task. Besides the needed infrastructure and expertise, effective delivery of a bioinformatics course could benefit from hands-on sessions, interactivity and problem-based learning approaches. Results In this article, we discuss the challenges and best practices in delivering bioinformatics training in resource-limited settings taking the example of hosting and running a multiple-delivery online course, Introduction to Bioinformatics, that was developed by the H3ABioNet Education and Training working group and delivered in 27 remote classrooms across Africa in 2017. We take the case of the University of Khartoum classrooms. Believing that our local setting is similar to others in less-developed countries, we also reflect upon aspects like classroom environment and recruitment of students to maximize outcomes.
Collapse
Affiliation(s)
- Azza E Ahmed
- Center for Bioinformatics and Systems Biology, Faculty of Science, University of Khartoum, Khartoum, Sudan.,Department of Electrical and Electronic Engineering, Faculty of Engineering, University of Khartoum, Sudan
| | - Ayah A Awadallah
- Department of Zoology, Faculty of Science, University of Khartoum, Khartoum, Sudan
| | - Mawada Tagelsir
- Department of Haematology and Immunohaematology, Faculty of Medical Laboratory Sciences, Ibn Sina University, Khartoum, Sudan
| | - Maram A Suliman
- Department of Biology, Faculty of Medicine, Ibn Sina University, Khartoum, Sudan
| | - Atheer Eltigani
- Department of Medical Biotechnology, Commission for Biotechnology and Genetic Engineering, National Centre for Research, Khartoum, Sudan
| | - Hassan Elsafi
- Medicinal, Aromatic Plants and Traditional Medicine Research Institute, National Centre for Research, Khartoum, Sudan
| | - Basil D Hamdelnile
- Center for Bioinformatics and Systems Biology, Faculty of Science, University of Khartoum, Khartoum, Sudan
| | | | - Faisal M Fadlelmola
- Center for Bioinformatics and Systems Biology, Faculty of Science, University of Khartoum, Khartoum, Sudan
| |
Collapse
|
32
|
Ten simple rules for teaching applied programming in an authentic and immersive online environment. PLoS Comput Biol 2021; 17:e1009184. [PMID: 34351897 PMCID: PMC8341656 DOI: 10.1371/journal.pcbi.1009184] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022] Open
|
33
|
Melendrez MC, Shaw S, Brown CT, Goodner BW, Kvaal C. Editorial: Curriculum Applications in Microbiology: Bioinformatics in the Classroom. Front Microbiol 2021; 12:705233. [PMID: 34276638 PMCID: PMC8281245 DOI: 10.3389/fmicb.2021.705233] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2021] [Accepted: 06/07/2021] [Indexed: 11/18/2022] Open
Affiliation(s)
| | - Sophie Shaw
- Centre for Genome Enabled Biology and Medicine, University of Aberdeen, Aberdeen, United Kingdom
| | - C Titus Brown
- Department of Population Health and Reproduction, University of California, Davis, Davis, CA, United States
| | | | - Christopher Kvaal
- Department of Biology, St. Cloud State University, St. Cloud, MN, United States
| |
Collapse
|
34
|
Wu P, Xu C, Chen H, Yang J, Zhang X, Zhou S. NOVOWrap: An automated solution for plastid genome assembly and structure standardization. Mol Ecol Resour 2021; 21:2177-2186. [PMID: 33934526 DOI: 10.1111/1755-0998.13410] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/27/2020] [Revised: 04/22/2021] [Accepted: 04/26/2021] [Indexed: 11/28/2022]
Abstract
Plastid genomes play an important role in genomics and evolutionary biology. Next-generation sequencing has revolutionized plastid genomic data acquisition to the point that genome assembly has become a bottleneck for widespread utilization of plastid genome data. To solve this problem, we developed an open-source, cross-platform tool known as, NOVOWrap, which includes both command-line and graphical interfaces for automatically assembling plastid genomes on personal computers. With minimal inputs, settings, and user intervention, NOVOWrap can automatically assemble plastid genomes, validate results and standardize the structure using affordable computer resources. The performance of this software has been successfully benchmarked against the plastid genomes of 11 species belonging to lycopods, gymnosperms, and angiosperms. By liberating researchers from laborious and cumbersome computer manipulations and create reliable and standardized genomic data, NOVOWrap is expected to accelerate plastid genome assembly, ease the process of data exchange, and contribute to downstream analysis.
Collapse
Affiliation(s)
- Ping Wu
- State Key Laboratory of Systematic and Evolutionary Botany, Institute of Botany, Chinese Academy of Sciences, Beijing, China.,University of Chinese Academy of Sciences, Beijing, China
| | - Chao Xu
- State Key Laboratory of Systematic and Evolutionary Botany, Institute of Botany, Chinese Academy of Sciences, Beijing, China
| | - Hao Chen
- Shaanxi University of Science and Technology, Xi'an, China
| | - Jie Yang
- State Key Laboratory of Systematic and Evolutionary Botany, Institute of Botany, Chinese Academy of Sciences, Beijing, China.,University of Chinese Academy of Sciences, Beijing, China
| | - Xianchun Zhang
- State Key Laboratory of Systematic and Evolutionary Botany, Institute of Botany, Chinese Academy of Sciences, Beijing, China.,University of Chinese Academy of Sciences, Beijing, China
| | - Shiliang Zhou
- State Key Laboratory of Systematic and Evolutionary Botany, Institute of Botany, Chinese Academy of Sciences, Beijing, China.,University of Chinese Academy of Sciences, Beijing, China
| |
Collapse
|
35
|
Abstract
Cell imaging has entered the 'Big Data' era. New technologies in light microscopy and molecular biology have led to an explosion in high-content, dynamic and multidimensional imaging data. Similar to the 'omics' fields two decades ago, our current ability to process, visualize, integrate and mine this new generation of cell imaging data is becoming a critical bottleneck in advancing cell biology. Computation, traditionally used to quantitatively test specific hypotheses, must now also enable iterative hypothesis generation and testing by deciphering hidden biologically meaningful patterns in complex, dynamic or high-dimensional cell image data. Data science is uniquely positioned to aid in this process. In this Perspective, we survey the rapidly expanding new field of data science in cell imaging. Specifically, we highlight how data science tools are used within current image analysis pipelines, propose a computation-first approach to derive new hypotheses from cell image data, identify challenges and describe the next frontiers where we believe data science will make an impact. We also outline steps to ensure broad access to these powerful tools - democratizing infrastructure availability, developing sensitive, robust and usable tools, and promoting interdisciplinary training to both familiarize biologists with data science and expose data scientists to cell imaging.
Collapse
Affiliation(s)
- Meghan K Driscoll
- Department of Bioinformatics, UT Southwestern Medical Center, Dallas, TX 75390, USA
| | - Assaf Zaritsky
- Department of Software and Information Systems Engineering, Ben-Gurion University of the Negev, Beer-Sheva 84105, Israel
| |
Collapse
|
36
|
Dill-McFarland KA, König SG, Mazel F, Oliver DC, McEwen LM, Hong KY, Hallam SJ. An integrated, modular approach to data science education in microbiology. PLoS Comput Biol 2021; 17:e1008661. [PMID: 33630850 PMCID: PMC7906378 DOI: 10.1371/journal.pcbi.1008661] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/04/2022] Open
Abstract
We live in an increasingly data-driven world, where high-throughput sequencing and mass spectrometry platforms are transforming biology into an information science. This has shifted major challenges in biological research from data generation and processing to interpretation and knowledge translation. However, postsecondary training in bioinformatics, or more generally data science for life scientists, lags behind current demand. In particular, development of accessible, undergraduate data science curricula has the potential to improve research and learning outcomes as well as better prepare students in the life sciences to thrive in public and private sector careers. Here, we describe the Experiential Data science for Undergraduate Cross-Disciplinary Education (EDUCE) initiative, which aims to progressively build data science competency across several years of integrated practice. Through EDUCE, students complete data science modules integrated into required and elective courses augmented with coordinated cocurricular activities. The EDUCE initiative draws on a community of practice consisting of teaching assistants (TAs), postdocs, instructors, and research faculty from multiple disciplines to overcome several reported barriers to data science for life scientists, including instructor capacity, student prior knowledge, and relevance to discipline-specific problems. Preliminary survey results indicate that even a single module improves student self-reported interest and/or experience in bioinformatics and computer science. Thus, EDUCE provides a flexible and extensible active learning framework for integration of data science curriculum into undergraduate courses and programs across the life sciences.
Collapse
Affiliation(s)
- Kimberly A Dill-McFarland
- Department of Microbiology and Immunology, University of British Columbia, Vancouver, British Columbia, Canada
- ECOSCOPE, University of British Columbia, Vancouver, British Columbia, Canada
| | - Stephan G König
- Department of Microbiology and Immunology, University of British Columbia, Vancouver, British Columbia, Canada
- ECOSCOPE, University of British Columbia, Vancouver, British Columbia, Canada
| | - Florent Mazel
- Department of Microbiology and Immunology, University of British Columbia, Vancouver, British Columbia, Canada
- ECOSCOPE, University of British Columbia, Vancouver, British Columbia, Canada
- Department of Botany and Biodiversity Centre, University of British Columbia, Vancouver, British Columbia, Canada
| | - David C Oliver
- Department of Microbiology and Immunology, University of British Columbia, Vancouver, British Columbia, Canada
| | - Lisa M McEwen
- Department of Microbiology and Immunology, University of British Columbia, Vancouver, British Columbia, Canada
- ECOSCOPE, University of British Columbia, Vancouver, British Columbia, Canada
- School of Health Information Science, Faculty of Human and Social Development, University of Victoria, Victoria, British Columbia, Canada
| | - Kris Y Hong
- Department of Microbiology and Immunology, University of British Columbia, Vancouver, British Columbia, Canada
- ECOSCOPE, University of British Columbia, Vancouver, British Columbia, Canada
| | - Steven J Hallam
- Department of Microbiology and Immunology, University of British Columbia, Vancouver, British Columbia, Canada
- ECOSCOPE, University of British Columbia, Vancouver, British Columbia, Canada
- Graduate Program in Bioinformatics, University of British Columbia, Genome Sciences Centre, Vancouver, British Columbia, Canada
- Genome Science and Technology Program, University of British Columbia, Vancouver, British Columbia, Canada
- Life Sciences Institute, University of British Columbia, Vancouver, British Columbia, Canada
| |
Collapse
|
37
|
Crisan A, Fiore-Gartland B, Tory M. Passing the Data Baton : A Retrospective Analysis on Data Science Work and Workers. IEEE TRANSACTIONS ON VISUALIZATION AND COMPUTER GRAPHICS 2021; 27:1860-1870. [PMID: 33048684 DOI: 10.1109/tvcg.2020.3030340] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/11/2023]
Abstract
Data science is a rapidly growing discipline and organizations increasingly depend on data science work. Yet the ambiguity around data science, what it is, and who data scientists are can make it difficult for visualization researchers to identify impactful research trajectories. We have conducted a retrospective analysis of data science work and workers as described within the data visualization, human computer interaction, and data science literature. From this analysis we synthesis a comprehensive model that describes data science work and breakdown to data scientists into nine distinct roles. We summarise and reflect on the role that visualization has throughout data science work and the varied needs of data scientists themselves for tooling support. Our findings are intended to arm visualization researchers with a more concrete framing of data science with the hope that it will help them surface innovative opportunities for impacting data science work. Data availability: https://osf.io/z2xpd/?view_only=87fa24be486a473884adb9ffbe8db4ec.
Collapse
|
38
|
Bioinformatics in Mexico: A diagnostic from the academic perspective and recommendations for a public policy. PLoS One 2020; 15:e0243531. [PMID: 33320879 PMCID: PMC7737905 DOI: 10.1371/journal.pone.0243531] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2019] [Accepted: 11/24/2020] [Indexed: 11/19/2022] Open
Abstract
In this work, we present a diagnostic analysis of strengths, weaknesses, opportunities and threats (SWOT) of the current state of Bioinformatics in Mexico. We conducted semi-structured interviews among researchers and academics with key expertise in this field, identified by bibliometric analyses and qualitative sampling techniques. Additionally, an online survey was conducted reaching a higher number of respondents. Among the relevant findings of our study, the lack of specialized human resources and technological infrastructure stood out, along with deficiencies in the number and quality of academic programs, scarce public investment and a weak relationship between public and private institutions. However, there are great opportunities for developing a national Bioinformatics to support different economic sectors. In our opinion, this work could be useful to favor a comprehensive network among Mexican researchers, in order to lay the foundations of a national strategy towards a well designed public policy.
Collapse
|
39
|
Abstract
Microbiome research projects are often interdisciplinary, involving fields such as microbiology, genetics, ecology, evolution, bioinformatics, and statistics. These research projects can be an excellent fit for undergraduate courses ranging from introductory biology labs to upper-level capstone courses. Microbiome research projects can attract the interest of students majoring in health and medical sciences, environmental sciences, and agriculture, and there are meaningful ties to real-world issues relating to human health, climate change, and environmental sustainability and resilience in pristine, fragile ecosystems to bustling urban centers. In this review, we will discuss the potential of microbiome research integrated into classes using a number of different modalities. Our experience scaling-up and implementing microbiome projects at a range of institutions across the US has provided us with insight and strategies for what works well and how to diminish common hurdles that are encountered when implementing undergraduate microbiome research projects. We will discuss how course-based microbiome research can be leveraged to help faculty make advances in their own research and professional development and the resources that are available to support faculty interested in integrating microbiome research into their courses.
Collapse
Affiliation(s)
- Theodore R Muth
- Department of Biology, Brooklyn College of The City University of New York, Brooklyn, NY, United States.,Molecular, Cellular, and Developmental Biology Department at The Graduate Center of The City University of New York, New York, NY, United States
| | - Avrom J Caplan
- Department of Biology, Dyson College of Arts and Sciences, Pace University, New York, NY, United States
| |
Collapse
|
40
|
Martins A, Fonseca MJ, Lemos M, Lencastre L, Tavares F. Bioinformatics-Based Activities in High School: Fostering Students' Literacy, Interest, and Attitudes on Gene Regulation, Genomics, and Evolution. Front Microbiol 2020; 11:578099. [PMID: 33162959 PMCID: PMC7591593 DOI: 10.3389/fmicb.2020.578099] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2020] [Accepted: 09/08/2020] [Indexed: 11/13/2022] Open
Abstract
The key role of bioinformatics in explaining biological phenomena calls for the need to rethink didactic approaches at high school aligned with a new scientific reality. Despite several initiatives to introduce bioinformatics in the classroom, there is still a lack of knowledge on their impact on students' learning gains, engagement, and motivation. In this study, we detail the effects of four bioinformatics laboratories tailored for high school biology classes named "Mining the Genome: Using Bioinformatics Tools in the Classroom to Support Student Discovery of Genes" on literacy, interest, and attitudes on 387 high school students. By exploring these laboratories, students get acquainted with bioinformatics and acknowledge that many bioinformatics tools can be intuitive for beginners. Furthermore, introducing comparative genomics in their learning practices contributed for a better understanding of curricular contents regarding the identification of genes, their regulation, and how to make evolutionary assumptions. Following the intervention, students were able to pinpoint bioinformatics tools required to identify genes in a genomics sequence, and most importantly, they were able to solve genomics-related misconceptions. Overall, students revealed a positive attitude regarding the integration of bioinformatics-based approaches in their learning practices, reinforcing their added value in educational approaches.
Collapse
Affiliation(s)
- Ana Martins
- Departamento de Biologia, FCUP-Faculdade de Ciências, Universidade do Porto, Porto, Portugal.,CIBIO-Centro de Investigação em Biodiversidade e Recursos Genéticos, InBIO-Laboratório Associado, Universidade do Porto, Vairão, Portugal
| | - Maria João Fonseca
- MHNC-UP-Museu de História Natural e da Ciência, Universidade do Porto, Porto, Portugal
| | - Marina Lemos
- FPCEUP-Faculdade de Psicologia e Ciências da Educação, Universidade do Porto, Porto, Portugal
| | - Leonor Lencastre
- FPCEUP-Faculdade de Psicologia e Ciências da Educação, Universidade do Porto, Porto, Portugal
| | - Fernando Tavares
- Departamento de Biologia, FCUP-Faculdade de Ciências, Universidade do Porto, Porto, Portugal.,CIBIO-Centro de Investigação em Biodiversidade e Recursos Genéticos, InBIO-Laboratório Associado, Universidade do Porto, Vairão, Portugal
| |
Collapse
|
41
|
Davies A, Hooley F, Causey-Freeman P, Eleftheriou I, Moulton G. Using interactive digital notebooks for bioscience and informatics education. PLoS Comput Biol 2020; 16:e1008326. [PMID: 33151926 PMCID: PMC7643937 DOI: 10.1371/journal.pcbi.1008326] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/08/2023] Open
Abstract
Interactive digital notebooks provide an opportunity for researchers and educators to carry out data analysis and report the results in a single digital format. Further to just being digital, the format allows for rich content to be created in order to interact with the code and data contained in such a notebook to form an educational narrative. This primer introduces some of the fundamental aspects involved in using Jupyter notebooks in an educational setting for teaching in the bio/health informatics disciplines. We also provide 2 case studies that detail how we used Jupyter notebooks to teach non-coders programming skills on a blended Master's degree module for a Health Informatics programme and a fully online distance learning unit on Programming for a postgraduate certificate (PG Cert) in Clinical Bioinformatics with a more technical audience.
Collapse
Affiliation(s)
- Alan Davies
- School of Health Sciences, University of Manchester, Manchester, United Kingdom
| | - Frances Hooley
- School of Health Sciences, University of Manchester, Manchester, United Kingdom
| | | | - Iliada Eleftheriou
- School of Health Sciences, University of Manchester, Manchester, United Kingdom
| | - Georgina Moulton
- School of Health Sciences, University of Manchester, Manchester, United Kingdom
| |
Collapse
|
42
|
Strategic vision for improving human health at The Forefront of Genomics. Nature 2020; 586:683-692. [PMID: 33116284 DOI: 10.1038/s41586-020-2817-4] [Citation(s) in RCA: 156] [Impact Index Per Article: 39.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2020] [Accepted: 09/04/2020] [Indexed: 12/20/2022]
Abstract
Starting with the launch of the Human Genome Project three decades ago, and continuing after its completion in 2003, genomics has progressively come to have a central and catalytic role in basic and translational research. In addition, studies increasingly demonstrate how genomic information can be effectively used in clinical care. In the future, the anticipated advances in technology development, biological insights, and clinical applications (among others) will lead to more widespread integration of genomics into almost all areas of biomedical research, the adoption of genomics into mainstream medical and public-health practices, and an increasing relevance of genomics for everyday life. On behalf of the research community, the National Human Genome Research Institute recently completed a multi-year process of strategic engagement to identify future research priorities and opportunities in human genomics, with an emphasis on health applications. Here we describe the highest-priority elements envisioned for the cutting-edge of human genomics going forward-that is, at 'The Forefront of Genomics'.
Collapse
|
43
|
Core competencies for clinical informaticians: A systematic review. Int J Med Inform 2020; 141:104237. [DOI: 10.1016/j.ijmedinf.2020.104237] [Citation(s) in RCA: 13] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2020] [Revised: 07/20/2020] [Accepted: 07/21/2020] [Indexed: 12/20/2022]
|
44
|
Puente-Sánchez F, García-García N, Tamames J. SQMtools: automated processing and visual analysis of 'omics data with R and anvi'o. BMC Bioinformatics 2020; 21:358. [PMID: 32795263 PMCID: PMC7430844 DOI: 10.1186/s12859-020-03703-2] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2020] [Accepted: 07/28/2020] [Indexed: 12/22/2022] Open
Abstract
BACKGROUND The dramatic decrease in sequencing costs over the last decade has boosted the adoption of high-throughput sequencing applications as a standard tool for the analysis of environmental microbial communities. Nowadays even small research groups can easily obtain raw sequencing data. After that, however, non-specialists are faced with the double challenge of choosing among an ever-increasing array of analysis methodologies, and navigating the vast amounts of results returned by these approaches. RESULTS Here we present a workflow that relies on the SqueezeMeta software for the automated processing of raw reads into annotated contigs and reconstructed genomes (bins). A set of custom scripts seamlessly integrates the output into the anvi'o analysis platform, allowing filtering and visual exploration of the results. Furthermore, we provide a software package with utility functions to expose the SqueezeMeta results to the R analysis environment. CONCLUSIONS Altogether, our workflow allows non-expert users to go from raw sequencing reads to custom plots with only a few powerful, flexible and well-documented commands.
Collapse
Affiliation(s)
- Fernando Puente-Sánchez
- Systems Biology Department, Centro Nacional de Biotecnología (CNB-CSIC), C/ Darwin n° 3, Campus de Cantoblanco, 28049, Madrid, Spain.
| | - Natalia García-García
- Systems Biology Department, Centro Nacional de Biotecnología (CNB-CSIC), C/ Darwin n° 3, Campus de Cantoblanco, 28049, Madrid, Spain
| | - Javier Tamames
- Systems Biology Department, Centro Nacional de Biotecnología (CNB-CSIC), C/ Darwin n° 3, Campus de Cantoblanco, 28049, Madrid, Spain
| |
Collapse
|
45
|
Bezuidenhout L, Quick R, Shanahan H. "Ethics When You Least Expect It": A Modular Approach to Short Course Data Ethics Instruction. SCIENCE AND ENGINEERING ETHICS 2020; 26:2189-2213. [PMID: 32067185 PMCID: PMC7417416 DOI: 10.1007/s11948-020-00197-2] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 02/13/2019] [Accepted: 02/10/2020] [Indexed: 06/10/2023]
Abstract
Data science skills are rapidly becoming a necessity in modern science. In response to this need, institutions and organizations around the world are developing research data science curricula to teach the programming and computational skills that are needed to build and maintain data infrastructures and maximize the use of available data. To date, however, few of these courses have included an explicit ethics component, and developing such components can be challenging. This paper describes a novel approach to teaching data ethics on short courses developed for the CODATA-RDA Schools for Research Data Science. The ethics content of these schools is centred on the concept of open and responsible (data) science citizenship that draws on virtue ethics to promote ethics of practice. Despite having little formal teaching time, this concept of citizenship is made central to the course by distributing ethics content across technical modules. Ethics instruction consists of a wide range of techniques, including stand-alone lectures, group discussions and mini-exercises linked to technical modules. This multi-level approach enables students to develop an understanding both of "responsible and open (data) science citizenship", and of how such responsibilities are implemented in daily research practices within their home environment. This approach successfully locates ethics within daily data science practice, and allows students to see how small actions build into larger ethical concerns. This emphasises that ethics are not something "removed from daily research" or the remit of data generators/end users, but rather are a vital concern for all data scientists.
Collapse
Affiliation(s)
- Louise Bezuidenhout
- Institute for Science, Innovation and Society, University of Oxford, Oxford, UK
| | - Robert Quick
- High Throughput Computing, Indiana University, Bloomington, IN USA
| | - Hugh Shanahan
- Department of Computer Science, Royal Holloway, University of London, London, UK
| |
Collapse
|
46
|
McClatchy S, Bass KM, Gatti DM, Moylan A, Churchill G. Nine quick tips for efficient bioinformatics curriculum development and training. PLoS Comput Biol 2020; 16:e1008007. [PMID: 32702019 PMCID: PMC7377369 DOI: 10.1371/journal.pcbi.1008007] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
Abstract
Biomedical research is becoming increasingly data driven. New technologies that generate large-scale, complex data are continually emerging and evolving. As a result, there is a concurrent need for training researchers to use and understand new computational tools. Here we describe an efficient and effective approach to developing curriculum materials that can be deployed in a research environment to meet this need.
Collapse
Affiliation(s)
- Susan McClatchy
- The Jackson Laboratory, Bar Harbor, Maine, United States of America
- * E-mail:
| | - Kristin M. Bass
- Rockman et al, San Francisco, California, United States of America
| | - Daniel M. Gatti
- College of the Atlantic, Bar Harbor, Maine, United States of America
| | - Adam Moylan
- Rockman et al, San Francisco, California, United States of America
| | - Gary Churchill
- The Jackson Laboratory, Bar Harbor, Maine, United States of America
| |
Collapse
|
47
|
Fitak RR, Antonides JD, Baitchman EJ, Bonaccorso E, Braun J, Kubiski S, Chiu E, Fagre AC, Gagne RB, Lee JS, Malmberg JL, Stenglein MD, Dusek RJ, Forgacs D, Fountain-Jones NM, Gilbertson MLJ, Worsley-Tonks KEL, Funk WC, Trumbo DR, Ghersi BM, Grimaldi W, Heisel SE, Jardine CM, Kamath PL, Karmacharya D, Kozakiewicz CP, Kraberger S, Loisel DA, McDonald C, Miller S, O'Rourke D, Ott-Conn CN, Páez-Vacas M, Peel AJ, Turner WC, VanAcker MC, VandeWoude S, Pecon-Slattery J. The Expectations and Challenges of Wildlife Disease Research in the Era of Genomics: Forecasting with a Horizon Scan-like Exercise. J Hered 2020; 110:261-274. [PMID: 31067326 DOI: 10.1093/jhered/esz001] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2018] [Accepted: 01/08/2019] [Indexed: 12/14/2022] Open
Abstract
The outbreak and transmission of disease-causing pathogens are contributing to the unprecedented rate of biodiversity decline. Recent advances in genomics have coalesced into powerful tools to monitor, detect, and reconstruct the role of pathogens impacting wildlife populations. Wildlife researchers are thus uniquely positioned to merge ecological and evolutionary studies with genomic technologies to exploit unprecedented "Big Data" tools in disease research; however, many researchers lack the training and expertise required to use these computationally intensive methodologies. To address this disparity, the inaugural "Genomics of Disease in Wildlife" workshop assembled early to mid-career professionals with expertise across scientific disciplines (e.g., genomics, wildlife biology, veterinary sciences, and conservation management) for training in the application of genomic tools to wildlife disease research. A horizon scanning-like exercise, an activity to identify forthcoming trends and challenges, performed by the workshop participants identified and discussed 5 themes considered to be the most pressing to the application of genomics in wildlife disease research: 1) "Improving communication," 2) "Methodological and analytical advancements," 3) "Translation into practice," 4) "Integrating landscape ecology and genomics," and 5) "Emerging new questions." Wide-ranging solutions from the horizon scan were international in scope, itemized both deficiencies and strengths in wildlife genomic initiatives, promoted the use of genomic technologies to unite wildlife and human disease research, and advocated best practices for optimal use of genomic tools in wildlife disease projects. The results offer a glimpse of the potential revolution in human and wildlife disease research possible through multi-disciplinary collaborations at local, regional, and global scales.
Collapse
Affiliation(s)
| | - Jennifer D Antonides
- Department of Forestry & Natural Resources, Purdue University, West Lafayette, IN
| | - Eric J Baitchman
- The Zoo New England Division of Animal Health and Conservation, Boston, MA
| | - Elisa Bonaccorso
- The Instituto BIOSFERA and Colegio de Ciencias Biológicas y Ambientales, Universidad San Francisco de Quito, vía Interoceánica y Diego de Robles, Quito, Ecuador
| | - Josephine Braun
- The Institute for Conservation Research, San Diego Zoo Global, Escondido, CA
| | - Steven Kubiski
- The Institute for Conservation Research, San Diego Zoo Global, Escondido, CA
| | - Elliott Chiu
- Department of Microbiology, Immunology and Pathology, Colorado State University, Fort Collins, CO
| | - Anna C Fagre
- Department of Microbiology, Immunology and Pathology, Colorado State University, Fort Collins, CO
| | - Roderick B Gagne
- Department of Microbiology, Immunology and Pathology, Colorado State University, Fort Collins, CO
| | - Justin S Lee
- Department of Microbiology, Immunology and Pathology, Colorado State University, Fort Collins, CO
| | - Jennifer L Malmberg
- Department of Microbiology, Immunology and Pathology, Colorado State University, Fort Collins, CO
| | - Mark D Stenglein
- Department of Microbiology, Immunology and Pathology, Colorado State University, Fort Collins, CO
| | - Robert J Dusek
- The U. S. Geological Survey, National Wildlife Health Center, Madison, WI
| | - David Forgacs
- The Interdisciplinary Graduate Program of Genetics, Texas A&M University, College Station, TX
| | | | - Marie L J Gilbertson
- The Department of Veterinary Population Medicine, University of Minnesota, St. Paul, MN
| | | | - W Chris Funk
- The Department of Biology, Colorado State University, Fort Collins, CO
| | - Daryl R Trumbo
- The Department of Biology, Colorado State University, Fort Collins, CO
| | | | | | - Sara E Heisel
- The Odum School of Ecology, University of Georgia, Athens, GA
| | - Claire M Jardine
- The Department of Pathobiology, Canadian Wildlife Health Cooperative, University of Guelph, Guelph, Ontario, Canada
| | - Pauline L Kamath
- The School of Food and Agriculture, University of Maine, Orono, ME
| | | | | | - Simona Kraberger
- The Biodesign Center for Fundamental and Applied Microbiomics, Center for Evolution and Medicine, School of Life Sciences, Arizona State University, Tempe, AZ
| | - Dagan A Loisel
- The Department of Biology, Saint Michael's College, Colchester, VT
| | - Cait McDonald
- The Department of Ecology & Evolutionary Biology, Cornell University, Ithaca, NY (McDonald)
| | - Steven Miller
- The Department of Biology, Drexel University, Philadelphia, PA
| | | | - Caitlin N Ott-Conn
- The Michigan Department of Natural Resources, Wildlife Disease Laboratory, Lansing, MI
| | - Mónica Páez-Vacas
- The Centro de Investigación de la Biodiversidad y Cambio Climático (BioCamb), Facultad de Ciencias de Medio Ambiente, Universidad Tecnológica Indoamérica, Machala y Sabanilla, Quito, Ecuador
| | - Alison J Peel
- The Environmental Futures Research Institute, Griffith University, Nathan, Queensland, Australia
| | - Wendy C Turner
- The Department of Biological Sciences, University at Albany, State University of New York, Albany, NY
| | - Meredith C VanAcker
- The Department of Ecology, Evolution, and Environmental Biology, Columbia University, New York, NY
| | - Sue VandeWoude
- The College of Veterinary Medicine and Biomedical Sciences, Colorado State University, Fort Collins, CO
| | - Jill Pecon-Slattery
- The Center for Species Survival, Smithsonian Conservation Biology Institute-National Zoological Park, Front Royal, VA
| |
Collapse
|
48
|
Carretero-Puche C, García-Martín S, García-Carbonero R, Gómez-López G, Al-Shahrour F. How can bioinformatics contribute to the routine application of personalized precision medicine? EXPERT REVIEW OF PRECISION MEDICINE AND DRUG DEVELOPMENT 2020. [DOI: 10.1080/23808993.2020.1758062] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/24/2022]
Affiliation(s)
- Carlos Carretero-Puche
- Bioinformatics Unit, Spanish National Cancer Research Centre (CNIO), Madrid, Spain
- Laboratorio de Oncología Clínico-Traslacional, Unidad de Investigación en Tumores Digestivos, Instituto de Investigación I+12, Hospital 12 de Octubre, Madrid, Spain
| | | | - Rocío García-Carbonero
- Laboratorio de Oncología Clínico-Traslacional, Unidad de Investigación en Tumores Digestivos, Instituto de Investigación I+12, Hospital 12 de Octubre, Madrid, Spain
| | - Gonzalo Gómez-López
- Bioinformatics Unit, Spanish National Cancer Research Centre (CNIO), Madrid, Spain
| | - Fátima Al-Shahrour
- Bioinformatics Unit, Spanish National Cancer Research Centre (CNIO), Madrid, Spain
| |
Collapse
|
49
|
Garcia L, Batut B, Burke ML, Kuzak M, Psomopoulos F, Arcila R, Attwood TK, Beard N, Carvalho-Silva D, Dimopoulos AC, del Angel VD, Dumontier M, Gurwitz KT, Krause R, McQuilton P, Le Pera L, Morgan SL, Rauste P, Via A, Kahlem P, Rustici G, van Gelder CWG, Palagi PM. Ten simple rules for making training materials FAIR. PLoS Comput Biol 2020; 16:e1007854. [PMID: 32437350 PMCID: PMC7241697 DOI: 10.1371/journal.pcbi.1007854] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023] Open
Abstract
Everything we do today is becoming more and more reliant on the use of computers. The field of biology is no exception; but most biologists receive little or no formal preparation for the increasingly computational aspects of their discipline. In consequence, informal training courses are often needed to plug the gaps; and the demand for such training is growing worldwide. To meet this demand, some training programs are being expanded, and new ones are being developed. Key to both scenarios is the creation of new course materials. Rather than starting from scratch, however, it's sometimes possible to repurpose materials that already exist. Yet finding suitable materials online can be difficult: They're often widely scattered across the internet or hidden in their home institutions, with no systematic way to find them. This is a common problem for all digital objects. The scientific community has attempted to address this issue by developing a set of rules (which have been called the Findable, Accessible, Interoperable and Reusable [FAIR] principles) to make such objects more findable and reusable. Here, we show how to apply these rules to help make training materials easier to find, (re)use, and adapt, for the benefit of all.
Collapse
Affiliation(s)
- Leyla Garcia
- ZB MED Information Centre for Life Sciences, Cologne, Germany
| | - Bérénice Batut
- Bioinformatics group, Department of Computer Science, University of Freiburg, Freiburg, Germany
| | - Melissa L. Burke
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridgeshire, United Kingdom
| | - Mateusz Kuzak
- Netherlands eScience Center, Amsterdam, the Netherlands
- Dutch Techcentre for Life Sciences, Utrecht, the Netherlands
| | - Fotis Psomopoulos
- Institute of Applied Biosciences, Centre for Research and Technology Hellas, Thessaloniki, Greece
| | - Ricardo Arcila
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridgeshire, United Kingdom
| | - Teresa K. Attwood
- Department of Computer Science, The University of Manchester, Manchester, United Kingdom
| | - Niall Beard
- Department of Computer Science, The University of Manchester, Manchester, United Kingdom
| | - Denise Carvalho-Silva
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridgeshire, United Kingdom
- Open Targets, Wellcome Genome Campus, Hinxton, United Kingdom
| | | | | | - Michel Dumontier
- Institute of Data Science, Maastricht University, Maastricht, the Netherlands
| | | | - Roland Krause
- University of Luxembourg, Esch-sur-Alzette, Luxembourg
| | - Peter McQuilton
- Oxford e-Research Centre, Department of Engineering Sciences, University of Oxford, United Kingdom
| | - Loredana Le Pera
- IBIOM-CNR, Bari, Italy
- IBPM-CNR, Sapienza Università di Roma, Roma, Italy
| | - Sarah L. Morgan
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridgeshire, United Kingdom
| | - Päivi Rauste
- CSC—IT Center for Science, Keilaranta, Espoo, Finland
| | - Allegra Via
- IBPM-CNR, Sapienza Università di Roma, Roma, Italy
| | - Pascal Kahlem
- Scientific Network Management S.L., Barcelona, Spain
| | | | | | - Patricia M. Palagi
- SIB Training group, SIB Swiss Institute of Bioinformatics, Lausanne, Switzerland
| |
Collapse
|
50
|
Tangaro MA, Donvito G, Antonacci M, Chiara M, Mandreoli P, Pesole G, Zambelli F. Laniakea: an open solution to provide Galaxy "on-demand" instances over heterogeneous cloud infrastructures. Gigascience 2020; 9:giaa033. [PMID: 32252069 PMCID: PMC7136032 DOI: 10.1093/gigascience/giaa033] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/10/2020] [Revised: 03/13/2020] [Accepted: 03/17/2020] [Indexed: 12/26/2022] Open
Abstract
BACKGROUND While the popular workflow manager Galaxy is currently made available through several publicly accessible servers, there are scenarios where users can be better served by full administrative control over a private Galaxy instance, including, but not limited to, concerns about data privacy, customisation needs, prioritisation of particular job types, tools development, and training activities. In such cases, a cloud-based Galaxy virtual instance represents an alternative that equips the user with complete control over the Galaxy instance itself without the burden of the hardware and software infrastructure involved in running and maintaining a Galaxy server. RESULTS We present Laniakea, a complete software solution to set up a "Galaxy on-demand" platform as a service. Building on the INDIGO-DataCloud software stack, Laniakea can be deployed over common cloud architectures usually supported both by public and private e-infrastructures. The user interacts with a Laniakea-based service through a simple front-end that allows a general setup of a Galaxy instance, and then Laniakea takes care of the automatic deployment of the virtual hardware and the software components. At the end of the process, the user gains access with full administrative privileges to a private, production-grade, fully customisable, Galaxy virtual instance and to the underlying virtual machine (VM). Laniakea features deployment of single-server or cluster-backed Galaxy instances, sharing of reference data across multiple instances, data volume encryption, and support for VM image-based, Docker-based, and Ansible recipe-based Galaxy deployments. A Laniakea-based Galaxy on-demand service, named Laniakea@ReCaS, is currently hosted at the ELIXIR-IT ReCaS cloud facility. CONCLUSIONS Laniakea offers to scientific e-infrastructures a complete and easy-to-use software solution to provide a Galaxy on-demand service to their users. Laniakea-based cloud services will help in making Galaxy more accessible to a broader user base by removing most of the burdens involved in deploying and running a Galaxy service. In turn, this will facilitate the adoption of Galaxy in scenarios where classic public instances do not represent an optimal solution. Finally, the implementation of Laniakea can be easily adapted and expanded to support different services and platforms beyond Galaxy.
Collapse
Affiliation(s)
- Marco Antonio Tangaro
- Institute of Biomembranes, Bioenergetics and Molecular Biotechnologies, National Research Council (CNR), Via Giovanni Amendola 122/O, 70126 Bari, Italy
| | - Giacinto Donvito
- National Institute for Nuclear Physics (INFN), Section of Bari, Via Orabona 4, 70126 Bari, Italy
| | - Marica Antonacci
- National Institute for Nuclear Physics (INFN), Section of Bari, Via Orabona 4, 70126 Bari, Italy
| | - Matteo Chiara
- Department of Biosciences, University of Milan, via Celoria 26, 20133 Milano, Italy
| | - Pietro Mandreoli
- Institute of Biomembranes, Bioenergetics and Molecular Biotechnologies, National Research Council (CNR), Via Giovanni Amendola 122/O, 70126 Bari, Italy
- Department of Biosciences, University of Milan, via Celoria 26, 20133 Milano, Italy
| | - Graziano Pesole
- Institute of Biomembranes, Bioenergetics and Molecular Biotechnologies, National Research Council (CNR), Via Giovanni Amendola 122/O, 70126 Bari, Italy
- Department of Biosciences, Biotechnologies and Biopharmaceutics, University of Bari, Via Orabona 4, 70126 Bari, Italy
| | - Federico Zambelli
- Institute of Biomembranes, Bioenergetics and Molecular Biotechnologies, National Research Council (CNR), Via Giovanni Amendola 122/O, 70126 Bari, Italy
- Department of Biosciences, University of Milan, via Celoria 26, 20133 Milano, Italy
| |
Collapse
|