1
|
Loyola Irizarry HG, Duarte H, Nakamura K, Benabentos R, McCartney M, Siltberg-Liberles J. A bioinformatics-driven CURE extension increases student self-efficacy and interest in biomedical research. JOURNAL OF MICROBIOLOGY & BIOLOGY EDUCATION 2025:e0023124. [PMID: 40207946 DOI: 10.1128/jmbe.00231-24] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/16/2024] [Accepted: 03/05/2025] [Indexed: 04/11/2025]
Abstract
The biology workforce has a need for undergraduate students trained in bioinformatics. Although bioinformatics is a critical sub-discipline of biology, it is not required in all biology degree programs. In parallel, there is a need to increase student access to research experiences. To address these needs, we offer a one-credit bioinformatics-focused and computational biology course-based undergraduate research experience (CURE), here called the CB-CURE. Preliminary data suggest the CB-CURE increased student interest, knowledge, and self-efficacy, but also reveal a shortage of access to undergraduate research experiences (UREs) in faculty labs at our large institution. To provide a more URE-like experience for a class setting, we developed a one-semester extension to the CB-CURE, called CURE+. In CURE+, students execute individual bioinformatics-driven research projects and obtain additional career development and mentoring. To evaluate CURE+, we measured students' bioinformatics and research self-efficacy, interest in bioinformatics and research, and emotions toward their project. Additionally, we evaluated student mastery of the CURE+ learning outcomes to determine if the experience successfully enabled students to develop their research skills. Our data show significant increases in (i) student self-efficacy in various bioinformatics and research skills and (ii) student interest in bioinformatics-related activities and in biomedical research. Students had positive emotions toward their research project, and a majority of students mastered the CURE+ learning outcomes. Our data suggest that an intensive CURE extension can provide a potentially transformative research experience that helps fill a void in access to research at institutions with a high student-to-faculty ratio.
Collapse
Affiliation(s)
- Héctor G Loyola Irizarry
- Department of Biological Sciences, Florida International University, Miami, Florida, USA
- STEM Transformation Institute, Florida International University, Miami, Florida, USA
| | - Hiram Duarte
- Department of Biological Sciences, Florida International University, Miami, Florida, USA
| | - Kyoko Nakamura
- Department of Biological Sciences, Florida International University, Miami, Florida, USA
| | - Rocio Benabentos
- STEM Transformation Institute, Florida International University, Miami, Florida, USA
| | - Melissa McCartney
- Department of Pharmacology and Toxicology, University at Buffalo, Buffalo, New York, USA
| | - Jessica Siltberg-Liberles
- Department of Biological Sciences, Florida International University, Miami, Florida, USA
- Biomolecular Sciences Institute, Florida International University, Miami, Florida, USA
| |
Collapse
|
2
|
Lee JS, Lowell JL, Whitewater K, Roane TM, Miller CS, Chan AP, Sylvester AW, Jackson D, Hunter LE. Monitoring environmental microbiomes: Alignment of microbiology and computational biology competencies within a culturally integrated curriculum and research framework. Mol Ecol Resour 2025; 25:e13867. [PMID: 37702134 PMCID: PMC11696487 DOI: 10.1111/1755-0998.13867] [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: 10/31/2022] [Revised: 08/18/2023] [Accepted: 08/30/2023] [Indexed: 09/14/2023]
Abstract
We have developed a flexible undergraduate curriculum that leverages the place-based research of environmental microbiomes to increase the number of Indigenous researchers in microbiology, data science and scientific computing. Monitoring Environmental Microbiomes (MEM) provides a curriculum and research framework designed to integrate an Indigenous approach when conducting authentic scientific research and to build interest and confidence at the undergraduate level. MEM has been successfully implemented as a short summer workshop to introduce computing practices in microbiome analysis. Based on self-assessed student knowledge of topics and skills, increased scientific confidence and interest in genomics careers were observed. We propose MEM be incorporated in a scalable course-based research experience for undergraduate institutions, including tribal colleges and universities, community colleges and other minority serving institutions. This coupled curricular and research framework explicitly considers cultural perspectives, access and equity to train a diverse future workforce that is more informed to engage in microbiome research and to translate microbiome science to benefit community and environmental health.
Collapse
Affiliation(s)
- J. S. Lee
- Department of Chemistry and BiochemistryFort Lewis CollegeDurangoColoradoUSA
| | - J. L. Lowell
- Department of Public HealthFort Lewis CollegeDurangoColoradoUSA
| | - K. Whitewater
- Department of Chemistry and BiochemistryFort Lewis CollegeDurangoColoradoUSA
| | - T. M. Roane
- Department of Integrative BiologyUniversity of Colorado DenverDenverColoradoUSA
| | - C. S. Miller
- Department of Integrative BiologyUniversity of Colorado DenverDenverColoradoUSA
| | - A. P. Chan
- J. Craig Venter InstituteRockvilleMarylandUSA
| | - A. W. Sylvester
- Marine Biological LaboratoryWoods HoleMassachusettsUSA
- University of WyomingLaramieWyomingUSA
| | - D. Jackson
- Cold Spring Harbor LaboratoryCold Spring HarborNew YorkUSA
| | - L. E. Hunter
- Department of Biomedical InformaticsUniversity of Colorado Anschutz Medical CampusAuroraColoradoUSA
| |
Collapse
|
3
|
Reed LK, Kleinschmit AJ, Buonaccorsi V, Hunt AG, Chalker D, Williams J, Jones CJ, Martinez-Cruzado JC, Rosenwald A. A genomics learning framework for undergraduates. PLoS One 2025; 20:e0313124. [PMID: 39787200 PMCID: PMC11717232 DOI: 10.1371/journal.pone.0313124] [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: 04/18/2024] [Accepted: 10/20/2024] [Indexed: 01/12/2025] Open
Abstract
Genomics is an increasingly important part of biology research. However, educating undergraduates in genomics is not yet a standard part of life sciences curricula. We believe this is, in part, due to a lack of standard concepts for the teaching of genomics. To address this deficit, the members of the Genomics Education Alliance created a set of genomics concepts that was then further refined by input from a community of undergraduate educators who engage in genomics instruction. The final genomics concepts list was compared to existing learning frameworks, including the Vision and Change initiative (V&C), as well as ones for genetics, biochemistry and molecular biology, and bioinformatics. Our results demonstrate that the new genomics framework fills a niche not addressed by previous inventories. This new framework should be useful to educators seeking to design stand-alone courses in genomics as well as those seeking to incorporate genomics into existing coursework. Future work will involve designing curriculum and assessments to go along with this genomics learning framework.
Collapse
Affiliation(s)
- Laura K. Reed
- Department of Biology, University of Alabama, Tuscaloosa, Alabama, United States of America
| | - Adam J. Kleinschmit
- Department of Natural and Applied Sciences, University of Dubuque, Dubuque, Iowa, United States of America
| | - Vincent Buonaccorsi
- Department of Biology, Juniata College, Huntingdon, Pennsylvania, United States of America
| | - Arthur G. Hunt
- Department of Plant and Soil Sciences, University of Kentucky, Lexington, Kentucky, United States of America
| | - Douglas Chalker
- Department of Biology, Washington University in St. Louis, St. Louis, Missouri, United States of America
| | - Jason Williams
- DNA Learning Center, Cold Spring Harbor Laboratory, Cold Spring Harbor, New York, United States of America
| | - Christopher J. Jones
- Department of Biological Sciences, Moravian University, Bethlehem, Pennsylvania, United States of America
| | | | - Anne Rosenwald
- Department of Biology, Georgetown University, Washington, DC, United States of America
| |
Collapse
|
4
|
Goclowski CL, Jakiela J, Collins T, Hiltemann S, Howells M, Loach M, Manning J, Moreno P, Ostrovsky A, Rasche H, Tekman M, Tyson G, Videm P, Bacon W. Galaxy as a gateway to bioinformatics: Multi-Interface Galaxy Hands-on Training Suite (MIGHTS) for scRNA-seq. Gigascience 2025; 14:giae107. [PMID: 39775842 PMCID: PMC11707610 DOI: 10.1093/gigascience/giae107] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2024] [Revised: 10/28/2024] [Accepted: 11/26/2024] [Indexed: 01/11/2025] Open
Abstract
BACKGROUND Bioinformatics is fundamental to biomedical sciences, but its mastery presents a steep learning curve for bench biologists and clinicians. Learning to code while analyzing data is difficult. The curve may be flattened by separating these two aspects and providing intermediate steps for budding bioinformaticians. Single-cell analysis is in great demand from biologists and biomedical scientists, as evidenced by the proliferation of training events, materials, and collaborative global efforts like the Human Cell Atlas. However, iterative analyses lacking reinstantiation, coupled with unstandardized pipelines, have made effective single-cell training a moving target. FINDINGS To address these challenges, we present a Multi-Interface Galaxy Hands-on Training Suite (MIGHTS) for single-cell RNA sequencing (scRNA-seq) analysis, which offers parallel analytical methods using a graphical interface (buttons) or code. With clear, interoperable materials, MIGHTS facilitates smooth transitions between environments. Bridging the biologist-programmer gap, MIGHTS emphasizes interdisciplinary communication for effective learning at all levels. Real-world data analysis in MIGHTS promotes critical thinking and best practices, while FAIR data principles ensure validation of results. MIGHTS is freely available, hosted on the Galaxy Training Network, and leverages Galaxy interfaces for analyses in both settings. Given the ongoing popularity of Python-based (Scanpy) and R-based (Seurat & Monocle) scRNA-seq analyses, MIGHTS enables analyses using both. CONCLUSIONS MIGHTS consists of 11 tutorials, including recordings, slide decks, and interactive visualizations, and a demonstrated track record of sustainability via regular updates and community collaborations. Parallel pathways in MIGHTS enable concurrent training of scientists at any programming level, addressing the heterogeneous needs of novice bioinformaticians.
Collapse
Affiliation(s)
- Camila L Goclowski
- Eccles Institute of Human Genetics, University of Utah, Salt Lake City, UT, 84112, USA
| | - Julia Jakiela
- School of Chemistry, University of Edinburgh, Edinburgh, EH9 3FJ, UK
| | - Tyler Collins
- Department of Computer Science, John Hopkins Medical Institution, Baltimore, MD, 21224, USA
| | - Saskia Hiltemann
- Erasmus Medical Center, Rotterdam, Zuid-Holland, 3015 GD, Netherlands
| | - Morgan Howells
- School of Computing & Communications, The Open University, Milton Keynes, Buckinghamshire, MK7 6AA, UK
| | - Marisa Loach
- School of Life, Health & Chemical Sciences, The Open University, Milton Keynes, Buckinghamshire, MK7 6AA, UK
| | - Jonathan Manning
- European Bioinformatics Institute, European Molecular Biology Laboratory, Hinxton, CB10 1SD, UK
| | - Pablo Moreno
- Early Computational Oncology, AstraZeneca, Cambridge, CB2 0AA, UK
| | - Alex Ostrovsky
- Department of Computer Science, John Hopkins Medical Institution, Baltimore, MD, 21224, USA
| | - Helena Rasche
- Erasmus Medical Center, Rotterdam, Zuid-Holland, 3015 GD, Netherlands
| | - Mehmet Tekman
- Division of Pharmacology and Toxicology, University of Freiburg, Freiburg im Breisgau, Baden-Württemberg, 79098, Germany
| | - Graeme Tyson
- School of Life, Health & Chemical Sciences, The Open University, Milton Keynes, Buckinghamshire, MK7 6AA, UK
| | - Pavankumar Videm
- Department of Computer Science, University of Freiburg, Freiburg im Breisgau,Baden-Württemberg, 79098, Germany
| | - Wendi Bacon
- School of Life, Health & Chemical Sciences, The Open University, Milton Keynes, Buckinghamshire, MK7 6AA, UK
| |
Collapse
|
5
|
Pandey S, Elliott SL, Liepkalns J, Taylor RT, Vanniasinkam T, Kleinschmit AJ, Justement LB, Lal A, Condry D, Bruns HA, Paustian T, Mixter PF, Sparks-Thissen RL, Sletten S, Wisenden BD. The ImmunoSkills Guide: Competencies for undergraduate immunology curricula. PLoS One 2024; 19:e0313339. [PMID: 39527543 PMCID: PMC11554037 DOI: 10.1371/journal.pone.0313339] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2024] [Accepted: 10/22/2024] [Indexed: 11/16/2024] Open
Abstract
Immune literacy garnered significant attention in recent years due to the threat posed by emerging infectious diseases. The pace of immunological discoveries and their relevance to society are substantial yet coordinated educational efforts have been rare. This motivated us to create a task force of educators to reflect on pedagogical approaches to teaching immunology and to draft, develop, and evaluate key competencies for undergraduate immunology education. The research questions addressed include: 1) Which competencies are considered important by educators? 2) Are the illustrative skills clear, accurate and well aligned with the core competencies listed in the Vision and Change report?; 3) What are the concerns of immunology educators about competencies and skills? We collected data on the draft competencies using surveys, focus groups, and interviews. The iterative revision phase followed the community review phase before finalizing the framework. Here, we report a hierarchical learning framework, with six core competencies, twenty illustrative skills, and companion immunology-specific example learning outcomes. Predominant themes from interviews and focus groups, which informed revisions of this framework are shared. With the growing need for immunology education across the sciences, the ImmunoSkills Guide and accompanying discussion can be used as a resource for educators, administrators and policymakers.
Collapse
Affiliation(s)
- Sumali Pandey
- Biosciences Department, Minnesota State University Moorhead, Moorhead, MN, United States of America
| | - Samantha L. Elliott
- Center for Inclusive Teaching and Learning and Department of Biology, St. Mary’s College of Maryland, St. Mary’s City, MD, United States of America
| | - Justine Liepkalns
- Department of Microbiology, Immunology, and Pathology, Colorado State University, Fort Collins, CO, United States of America
| | - Rebekah T. Taylor
- Department of Biology, Frostburg State University, Frostburg, MD, United States of America
| | - Thiru Vanniasinkam
- School of Dentistry and Medical Sciences, Charles Sturt University, Bathurst, NSW, Australia
| | - Adam J. Kleinschmit
- Department of Natural and Applied Sciences, University of Dubuque, Dubuque, IA, United States of America
| | - Louis B. Justement
- Department of Microbiology, The University of Alabama at Birmingham, Heersink School of Medicine, Birmingham, AL, United States of America
| | - Archana Lal
- Department of Biology, Labette Community College, Parsons, KS, United States of America
| | - Danielle Condry
- Department of Microbiological Sciences, North Dakota State University, Fargo, ND, United States of America
| | - Heather A. Bruns
- Department of Microbiology, The University of Alabama at Birmingham, Heersink School of Medicine, Birmingham, AL, United States of America
| | - Timothy Paustian
- Department of Bacteriology, University of Wisconsin-Madison, Madison, WI, United States of America
| | - Philip F. Mixter
- School of Molecular Biosciences, College of Veterinary Medicine, Washington State University, Pullman, WA, United States of America
| | - Rebecca L. Sparks-Thissen
- Departments of Microbiology and Immunology and Pathology and Laboratory Medicine, Indiana University School of Medicine- Evansville, Evansville, IN, United States of America
| | - Sarah Sletten
- Department of Biomedical Sciences, School of Medicine & Health Sciences, University of North Dakota, Grand Forks, ND, United States of America
| | - Brian D. Wisenden
- Biosciences Department, Minnesota State University Moorhead, Moorhead, MN, United States of America
| |
Collapse
|
6
|
Plaisier SB, Alarid DO, Denning JA, Brownell SE, Buetow KH, Cooper KM, Wilson MA. Design and implementation of an asynchronous online course-based undergraduate research experience (CURE) in computational genomics. PLoS Comput Biol 2024; 20:e1012384. [PMID: 39264874 PMCID: PMC11392228 DOI: 10.1371/journal.pcbi.1012384] [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] [Indexed: 09/14/2024] Open
Abstract
As genomics technologies advance, there is a growing demand for computational biologists trained for genomics analysis but instructors face significant hurdles in providing formal training in computer programming, statistics, and genomics to biology students. Fully online learners represent a significant and growing community that can contribute to meet this need, but they are frequently excluded from valuable research opportunities which mostly do not offer the flexibility they need. To address these opportunity gaps, we developed an asynchronous course-based undergraduate research experience (CURE) for computational genomics specifically for fully online biology students. We generated custom learning materials and leveraged remotely accessible computational tools to address 2 novel research questions over 2 iterations of the genomics CURE, one testing bioinformatics approaches and one mining cancer genomics data. Here, we present how the instructional team distributed analysis needed to address these questions between students over a 7.5-week CURE and provided concurrent training in biology and statistics, computer programming, and professional development. Scores from identical learning assessments administered before and after completion of each CURE showed significant learning gains across biology and coding course objectives. Open-response progress reports were submitted weekly and identified self-reported adaptive coping strategies for challenges encountered throughout the course. Progress reports identified problems that could be resolved through collaboration with instructors and peers via messaging platforms and virtual meetings. We implemented asynchronous communication using the Slack messaging platform and an asynchronous journal club where students discussed relevant publications using the Perusall social annotation platform. The online genomics CURE resulted in unanticipated positive outcomes, including students voluntarily discussing plans to continue research after the course. These outcomes underscore the effectiveness of this genomics CURE for scientific training, recruitment and student-mentor relationships, and student successes. Asynchronous genomics CUREs can contribute to a more skilled, diverse, and inclusive workforce for the advancement of biomedical science.
Collapse
Affiliation(s)
- Seema B. Plaisier
- School of Life Sciences, Arizona State University, Tempe, Arizona, United States of America
- Center for Evolution and Medicine, Arizona State University, Tempe, Arizona, United States of America
| | - Danielle O. Alarid
- School of Life Sciences, Arizona State University, Tempe, Arizona, United States of America
- Center for Evolution and Medicine, Arizona State University, Tempe, Arizona, United States of America
| | - Joelle A. Denning
- School of Life Sciences, Arizona State University, Tempe, Arizona, United States of America
- Center for Evolution and Medicine, Arizona State University, Tempe, Arizona, United States of America
| | - Sara E. Brownell
- School of Life Sciences, Arizona State University, Tempe, Arizona, United States of America
- Research for Inclusive STEM Education Center, Arizona State University, Tempe, Arizona, United States of America
| | - Kenneth H. Buetow
- School of Life Sciences, Arizona State University, Tempe, Arizona, United States of America
- Center for Evolution and Medicine, Arizona State University, Tempe, Arizona, United States of America
| | - Katelyn M. Cooper
- School of Life Sciences, Arizona State University, Tempe, Arizona, United States of America
- Research for Inclusive STEM Education Center, Arizona State University, Tempe, Arizona, United States of America
| | - Melissa A. Wilson
- School of Life Sciences, Arizona State University, Tempe, Arizona, United States of America
- Center for Evolution and Medicine, Arizona State University, Tempe, Arizona, United States of America
| |
Collapse
|
7
|
Boland DJ, Ayres NM. Cracking AlphaFold2: Leveraging the power of artificial intelligence in undergraduate biochemistry curriculums. PLoS Comput Biol 2024; 20:e1012123. [PMID: 38935611 PMCID: PMC11210786 DOI: 10.1371/journal.pcbi.1012123] [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] [Indexed: 06/29/2024] Open
Abstract
AlphaFold2 is an Artificial Intelligence-based program developed to predict the 3D structure of proteins given only their amino acid sequence at atomic resolution. Due to the accuracy and efficiency at which AlphaFold2 can generate 3D structure predictions and its widespread adoption into various aspects of biochemical research, the technique of protein structure prediction should be considered for incorporation into the undergraduate biochemistry curriculum. A module for introducing AlphaFold2 into a senior-level biochemistry laboratory classroom was developed. The module's focus was to have students predict the structures of proteins from the MPOX 22 global outbreak virus isolate genome, which had no structures elucidated at that time. The goal of this study was to both determine the impact the module had on students and to develop a framework for introducing AlphaFold2 into the undergraduate curriculum so that instructors for biochemistry courses, regardless of their background in bioinformatics, could adapt the module into their classrooms.
Collapse
Affiliation(s)
- Devon J. Boland
- Department of Biochemistry & Biophysics, Texas A&M University, College Station, Texas, United States of America
| | - Nicola M. Ayres
- Department of Biochemistry & Biophysics, Texas A&M University, College Station, Texas, United States of America
| |
Collapse
|
8
|
Yang MA, Korsnack K. Pairing a bioinformatics-focused course-based undergraduate research experience with specifications grading in an introductory biology classroom. Biol Methods Protoc 2024; 9:bpae013. [PMID: 38463936 PMCID: PMC10924719 DOI: 10.1093/biomethods/bpae013] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/28/2023] [Revised: 01/27/2024] [Accepted: 02/22/2024] [Indexed: 03/12/2024] Open
Abstract
Introducing bioinformatics-focused concepts and skills in a biology classroom is difficult, especially in introductory biology classrooms. Course-based Undergraduate Research Experiences (CUREs) facilitate this process, introducing genomics and bioinformatics through authentic research experiences, but the many learning objectives needed in scientific research and communication, foundational biology concepts, and bioinformatics-focused concepts and skills can make the process challenging. Here, the pairing of specifications grading with a bioinformatics-focused CURE developed by the Genomics Education Partnership is described. The study examines how the course structure with specifications grading facilitated scaffolding of writing assignments, group work, and metacognitive activities; and describes the synergies between CUREs and specifications grading. CUREs require mastery of related concepts and skills for working through the research process, utilize common research practices of revision and iteration, and encourage a growth mindset to learning-all of which are heavily incentivized in assessment practices focused on specifications grading.
Collapse
Affiliation(s)
- Melinda A Yang
- Department of Biology, University of Richmond, Richmond, VA 23173, United States
| | - Kylie Korsnack
- Teaching and Scholarship Hub, University of Richmond, Richmond, VA 23173, United States
| |
Collapse
|
9
|
Patel P, Pillai N, Toby I. No-boundary thinking for artificial intelligence in bioinformatics and education. FRONTIERS IN BIOINFORMATICS 2024; 3:1332902. [PMID: 38259432 PMCID: PMC10800434 DOI: 10.3389/fbinf.2023.1332902] [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: 11/03/2023] [Accepted: 12/19/2023] [Indexed: 01/24/2024] Open
Abstract
No-boundary thinking enables the scientific community to reflect in a thoughtful manner and discover new opportunities, create innovative solutions, and break through barriers that might have otherwise constrained their progress. This concept encourages thinking without being confined by traditional rules, limitations, or established norms, and a mindset that is not limited by previous work, leading to fresh perspectives and innovative outcomes. So, where do we see the field of artificial intelligence (AI) in bioinformatics going in the next 30 years? That was the theme of a "No-Boundary Thinking" Session as part of the Mid-South Computational Bioinformatics Society's (MCBIOS) 19th annual meeting in Irving, Texas. This session addressed various areas of AI in an open discussion and raised some perspectives on how popular tools like ChatGPT can be integrated into bioinformatics, communicating with scientists in different fields to properly utilize the potential of these algorithms, and how to continue educational outreach to further interest of data science and informatics to the next-generation of scientists.
Collapse
Affiliation(s)
- Prajay Patel
- Chemistry Department, University of Dallas, Irving, TX, United States
| | - Nisha Pillai
- Department of Computer Science, Mississippi State University, Starkville, MS, United States
| | - Inimary Toby
- Biology Department, University of Dallas, Irving, TX, United States
| |
Collapse
|
10
|
Samuel S, Mietchen D. Computational reproducibility of Jupyter notebooks from biomedical publications. Gigascience 2024; 13:giad113. [PMID: 38206590 PMCID: PMC10783158 DOI: 10.1093/gigascience/giad113] [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: 10/05/2022] [Revised: 08/09/2023] [Accepted: 12/08/2023] [Indexed: 01/12/2024] Open
Abstract
BACKGROUND Jupyter notebooks facilitate the bundling of executable code with its documentation and output in one interactive environment, and they represent a popular mechanism to document and share computational workflows, including for research publications. The reproducibility of computational aspects of research is a key component of scientific reproducibility but has not yet been assessed at scale for Jupyter notebooks associated with biomedical publications. APPROACH We address computational reproducibility at 2 levels: (i) using fully automated workflows, we analyzed the computational reproducibility of Jupyter notebooks associated with publications indexed in the biomedical literature repository PubMed Central. We identified such notebooks by mining the article's full text, trying to locate them on GitHub, and attempting to rerun them in an environment as close to the original as possible. We documented reproduction success and exceptions and explored relationships between notebook reproducibility and variables related to the notebooks or publications. (ii) This study represents a reproducibility attempt in and of itself, using essentially the same methodology twice on PubMed Central over the course of 2 years, during which the corpus of Jupyter notebooks from articles indexed in PubMed Central has grown in a highly dynamic fashion. RESULTS Out of 27,271 Jupyter notebooks from 2,660 GitHub repositories associated with 3,467 publications, 22,578 notebooks were written in Python, including 15,817 that had their dependencies declared in standard requirement files and that we attempted to rerun automatically. For 10,388 of these, all declared dependencies could be installed successfully, and we reran them to assess reproducibility. Of these, 1,203 notebooks ran through without any errors, including 879 that produced results identical to those reported in the original notebook and 324 for which our results differed from the originally reported ones. Running the other notebooks resulted in exceptions. CONCLUSIONS We zoom in on common problems and practices, highlight trends, and discuss potential improvements to Jupyter-related workflows associated with biomedical publications.
Collapse
Affiliation(s)
- Sheeba Samuel
- Heinz-Nixdorf Chair for Distributed Information Systems, Friedrich Schiller University Jena, Jena 07743, Germany
- Michael Stifel Center Jena, Jena 07743, Germany
| | - Daniel Mietchen
- Ronin Institute, Montclair 07043-2314, NJ, United States
- Institute for Globally Distributed Open Research and Education (IGDORE)
- FIZ Karlsruhe—Leibniz Institute for Information Infrastructure, Berlin 76344, Germany
| |
Collapse
|
11
|
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: 11] [Impact Index Per Article: 5.5] [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
|
12
|
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
|
13
|
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
|
14
|
Sano T, Sampad MJN, Gonzalez-Ferrer J, Hernandez S, Vera-Choqqueccota S, Vargas PA, Urcuyo R, Duran NM, Teodorescu M, Haussler D, Schmidt H, Mostajo-Radji MA. Open-loop lab-on-a-chip technology enables remote computer science training in Latinx life sciences students. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.04.28.538776. [PMID: 37205466 PMCID: PMC10187215 DOI: 10.1101/2023.04.28.538776] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/21/2023]
Abstract
Despite many interventions, science education remains highly inequitable throughout the world. Among all life sciences fields, Bioinformatics and Computational Biology suffer from the strongest underrepresentation of racial and gender minorities. Internet-enabled project-based learning (PBL) has the potential to reach underserved communities and increase the diversity of the scientific workforce. Here, we demonstrate the use of lab-on-a-chip (LoC) technologies to train Latinx life science undergraduate students in concepts of computer programming by taking advantage of open-loop cloud-integrated LoCs. We developed a context-aware curriculum to train students at over 8,000 km from the experimental site. We showed that this approach was sufficient to develop programming skills and increase the interest of students in continuing careers in Bioinformatics. Altogether, we conclude that LoC-based Internet-enabled PBL can become a powerful tool to train Latinx students and increase the diversity in STEM.
Collapse
Affiliation(s)
- Tyler Sano
- Department of Electrical and Computer Engineering, University of California Santa Cruz, Santa Cruz, CA, 95064
| | | | - Jesus Gonzalez-Ferrer
- Department of Biomolecular Engineering, University of California Santa Cruz, Santa Cruz, CA, 95060
- Genomics Institute, University of California Santa Cruz, Santa Cruz, CA, 95060
- Live Cell Biotechnology Discovery Lab, University of California Santa Cruz, Santa Cruz, CA, 95060
| | - Sebastian Hernandez
- Department of Electrical and Computer Engineering, University of California Santa Cruz, Santa Cruz, CA, 95064
- Genomics Institute, University of California Santa Cruz, Santa Cruz, CA, 95060
- Live Cell Biotechnology Discovery Lab, University of California Santa Cruz, Santa Cruz, CA, 95060
- Centro de Electroquímica y Energía Química (CELEQ), Universidad de Costa Rica, San José, 11501 2060, Costa Rica
| | - Samira Vera-Choqqueccota
- Department of Biomolecular Engineering, University of California Santa Cruz, Santa Cruz, CA, 95060
- Genomics Institute, University of California Santa Cruz, Santa Cruz, CA, 95060
- Live Cell Biotechnology Discovery Lab, University of California Santa Cruz, Santa Cruz, CA, 95060
| | - Paola A Vargas
- Biotechnology, Universidad Católica Boliviana San Pablo, Santa Cruz de la Sierra, Bolivia
| | - Roberto Urcuyo
- Centro de Electroquímica y Energía Química (CELEQ), Universidad de Costa Rica, San José, 11501 2060, Costa Rica
| | | | - Mircea Teodorescu
- Department of Electrical and Computer Engineering, University of California Santa Cruz, Santa Cruz, CA, 95064
- Department of Biomolecular Engineering, University of California Santa Cruz, Santa Cruz, CA, 95060
- Genomics Institute, University of California Santa Cruz, Santa Cruz, CA, 95060
- Live Cell Biotechnology Discovery Lab, University of California Santa Cruz, Santa Cruz, CA, 95060
| | - David Haussler
- Department of Biomolecular Engineering, University of California Santa Cruz, Santa Cruz, CA, 95060
- Genomics Institute, University of California Santa Cruz, Santa Cruz, CA, 95060
- Live Cell Biotechnology Discovery Lab, University of California Santa Cruz, Santa Cruz, CA, 95060
| | - Holger Schmidt
- Department of Electrical and Computer Engineering, University of California Santa Cruz, Santa Cruz, CA, 95064
| | - Mohammed A Mostajo-Radji
- Genomics Institute, University of California Santa Cruz, Santa Cruz, CA, 95060
- Live Cell Biotechnology Discovery Lab, University of California Santa Cruz, Santa Cruz, CA, 95060
| |
Collapse
|
15
|
Timpe LC. An online Google Colab project for exploring the SARS CoV-2 genome and mRNA vaccines. BIOCHEMISTRY AND MOLECULAR BIOLOGY EDUCATION : A BIMONTHLY PUBLICATION OF THE INTERNATIONAL UNION OF BIOCHEMISTRY AND MOLECULAR BIOLOGY 2023; 51:209-211. [PMID: 36692038 DOI: 10.1002/bmb.21711] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/06/2022] [Accepted: 12/27/2022] [Indexed: 06/17/2023]
Affiliation(s)
- Leslie C Timpe
- Department of Biology, San Francisco State University, San Francisco, California, USA
| |
Collapse
|
16
|
Nanjala R, Nyasimi F, Masiga D, Kibet CK. A mentorship and incubation program using project-based learning to build a professional bioinformatics pipeline in Kenya. PLoS Comput Biol 2023; 19:e1010904. [PMID: 36862660 PMCID: PMC9980751 DOI: 10.1371/journal.pcbi.1010904] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/03/2023] Open
Abstract
The demand for well-trained bioinformaticians to support genomics research continues to rise. Unfortunately, undergraduate training in Kenya does not prepare students for specialization in bioinformatics. Graduates are often unaware of the career opportunities in bioinformatics, and those who are may lack mentors to help them choose a specialization. The Bioinformatics Mentorship and Incubation Program seeks to bridge the gap by laying the foundation for a bioinformatics training pipeline using project-based learning. The program selects six participants through an intensive open recruitment exercise for highly competitive students to join the program for four months. The six interns undergo intensive training within the first one and a half months before being assigned to mini-projects. We track the progress of the interns weekly through code review sessions and a final presentation at the end of the four months. We have trained five cohorts, most of whom have secured master's scholarships within and outside the country and job opportunities. We demonstrate the benefit of structured mentorship using project-based learning in filling the training gap after undergraduate programs to generate well-trained bioinformaticians who are competitive in graduate programs and bioinformatics jobs.
Collapse
Affiliation(s)
- Ruth Nanjala
- International Centre of Insect Physiology and Ecology, Nairobi, Kenya
- Kennedy Institute for Rheumatology, Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences, University of Oxford, United Kingdom
| | - Festus Nyasimi
- International Centre of Insect Physiology and Ecology, Nairobi, Kenya
- The University of Chicago, Chicago, Illinois, United States of America
| | - Daniel Masiga
- International Centre of Insect Physiology and Ecology, Nairobi, Kenya
| | | |
Collapse
|
17
|
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
|
18
|
Diversifying the genomic data science research community. Genome Res 2022; 32:1231-1241. [PMID: 35858750 PMCID: PMC9341509 DOI: 10.1101/gr.276496.121] [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] [Received: 01/19/2022] [Accepted: 06/02/2022] [Indexed: 11/25/2022]
Abstract
Over the past 20 years, the explosion of genomic data collection and the cloud computing revolution have made computational and data science research accessible to anyone with a web browser and an internet connection. However, students at institutions with limited resources have received relatively little exposure to curricula or professional development opportunities that lead to careers in genomic data science. To broaden participation in genomics research, the scientific community needs to support these programs in local education and research at underserved institutions (UIs). These include community colleges, historically Black colleges and universities, Hispanic-serving institutions, and tribal colleges and universities that support ethnically, racially, and socioeconomically underrepresented students in the United States. We have formed the Genomic Data Science Community Network to support students, faculty, and their networks to identify opportunities and broaden access to genomic data science. These opportunities include expanding access to infrastructure and data, providing UI faculty development opportunities, strengthening collaborations among faculty, recognizing UI teaching and research excellence, fostering student awareness, developing modular and open-source resources, expanding course-based undergraduate research experiences (CUREs), building curriculum, supporting student professional development and research, and removing financial barriers through funding programs and collaborator support.
Collapse
|
19
|
Reyes RJ, Hosmane N, Ihorn S, Johnson M, Kulkarni A, Nelson J, Savvides M, Ta D, Yoon I, Pennings PS. Ten simple rules for designing and running a computing minor for bio/chem students. PLoS Comput Biol 2022; 18:e1010202. [PMID: 35834439 PMCID: PMC9282537 DOI: 10.1371/journal.pcbi.1010202] [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: 11/29/2022] Open
Abstract
Science students increasingly need programming and data science skills to be competitive in the modern workforce. However, at our university (San Francisco State University), until recently, almost no biology, biochemistry, and chemistry students (from here bio/chem students) completed a minor in computer science. To change this, a new minor in computing applications, which is informally known as the Promoting Inclusivity in Computing (PINC) minor, was established in 2016. Here, we present the lessons we learned from our experience in a set of 10 rules. The first 3 rules focus on setting up the program so that it interests students in biology, chemistry, and biochemistry. Rules 4 through 8 focus on how the classes of the program are taught to make them interesting for our students and to provide the students with the support they need. The last 2 rules are about what happens “behind the scenes” of running a program with many people from several departments involved.
Collapse
Affiliation(s)
- Rochelle-Jan Reyes
- Department of Biology, San Francisco State University, San Francisco, California, United States of America
- Department of Computer Science, San Francisco State University, San Francisco, California, United States of America
- Herbert Wertheim School of Public Health and Human Longevity Science, UC San Diego, San Diego, California, United States of America
| | - Nina Hosmane
- Department of Biology, San Francisco State University, San Francisco, California, United States of America
| | - Shasta Ihorn
- Department of Biology, San Francisco State University, San Francisco, California, United States of America
| | - Milo Johnson
- Department of Computer Science, San Francisco State University, San Francisco, California, United States of America
- Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, Massachusetts, United States of America
- Department of Integrative Biology, University of California, Berkeley, California, United States of America
| | - Anagha Kulkarni
- Department of Computer Science, San Francisco State University, San Francisco, California, United States of America
| | - Jennifer Nelson
- Department of Biology, San Francisco State University, San Francisco, California, United States of America
- Department of Computer Science, San Francisco State University, San Francisco, California, United States of America
| | - Michael Savvides
- Department of Computer Science, San Francisco State University, San Francisco, California, United States of America
| | - Duc Ta
- Department of Computer Science, San Francisco State University, San Francisco, California, United States of America
| | - Ilmi Yoon
- Department of Computer Science, San Francisco State University, San Francisco, California, United States of America
| | - Pleuni S. Pennings
- Department of Biology, San Francisco State University, San Francisco, California, United States of America
- * E-mail:
| |
Collapse
|
20
|
Forrester C, Schwikert S, Foster J, Corwin L. Undergraduate R Programming Anxiety in Ecology: Persistent Gender Gaps and Coping Strategies. CBE LIFE SCIENCES EDUCATION 2022; 21:ar29. [PMID: 35426729 PMCID: PMC9508917 DOI: 10.1187/cbe.21-05-0133] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/24/2021] [Revised: 02/22/2022] [Accepted: 03/03/2022] [Indexed: 06/14/2023]
Abstract
The ability to program in R, an open-source statistical program, is increasingly valued across job markets, including ecology. The benefits of teaching R to undergraduates are abundant, but learning to code in R may induce anxiety for students, potentially leading to negative learning outcomes and disengagement. Anecdotes suggest a gender differential in programming anxiety, with women experiencing greater anxiety. Currently, we do not know the extent to which programming anxiety exists in our undergraduate biology classrooms, whether it differs by gender, and what instructors can do to alleviate it. Instructor immediacy has been shown to mediate related anxieties such as quantitative and computer anxiety. Likewise, students' use of adaptive coping strategies may mitigate anxieties. We investigated students' R anxiety within a lower-division ecology course and explored its relationships with gender, instructor immediacy, classroom engagement, and reported coping strategies. Women reported significantly higher R anxiety than men, a gap that narrowed, yet persisted over the semester. In addition, several specific coping skills were associated with decreases in R anxiety and increases in self-concept and sense of control; these differed by gender identity. Our findings can guide future work to identify interventions that lessen programming anxiety in biology classes, especially for women.
Collapse
Affiliation(s)
| | - Shane Schwikert
- Office of Information Technology, University of Colorado Boulder, Boulder, CO 80309
| | | | - Lisa Corwin
- Department of Ecology and Evolutionary Biology, University of Colorado Boulder, Boulder, CO 80309
| |
Collapse
|
21
|
Chen A, Phillips KA, Schaefer JE, Sonner PM. The Development of Core Concepts for Neuroscience Higher Education: From Beginning to Summer Virtual Meeting Satellite Session. JOURNAL OF UNDERGRADUATE NEUROSCIENCE EDUCATION : JUNE : A PUBLICATION OF FUN, FACULTY FOR UNDERGRADUATE NEUROSCIENCE 2022; 20:A161-A165. [PMID: 38323056 PMCID: PMC10653233 DOI: 10.59390/ghor4737] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Received: 01/14/2020] [Revised: 03/08/2021] [Accepted: 03/29/2021] [Indexed: 02/08/2024]
Abstract
Neuroscience curricula vary widely across higher education institutions due to the lack of an accrediting body or a set of unified educational concepts or outcomes. Each institution has developed a unique set of fundamental knowledge, topical subdisciplines, and core competencies to be delivered in a neuroscience program. Core concepts would provide neuroscience departments and programs with a generally agreed upon set of overarching principles that organize knowledge and can be applied to all sub-disciplines of the field, providing a useful framework from which to approach neuroscience education. We set out to develop a consensus set of neuroscience core concepts to aid in higher education curricular development and assessment. Suggestions for neuroscience core concepts were solicited from neuroscience faculty in a nationwide survey and analyzed using an inductive, independent coding model to identify eight core concepts based upon survey responses. Accompanying explanatory paragraphs for each core concept were developed through an iterative process. We presented the resulting core concepts to 134 neuroscience educators at a satellite session of the Faculty for Undergraduate Neuroscience 2020 Summer Virtual Meeting (SVM). Individuals and groups of faculty provided feedback regarding the accuracy, comprehensiveness, and clarity of each concept and explanatory paragraph, as well as the structure of the document as a whole. We continue to refine the core concepts based upon this feedback and will distribute the final document in a subsequent publication. Following publication of the finalized list of core concepts, we will develop tools to help educators incorporate the core concepts into their curricula.
Collapse
Affiliation(s)
- Audrey Chen
- Neurobiology and Behavior Department, School of Biological Sciences, University of California, Irvine CA, 92697
| | | | - Jennifer E. Schaefer
- Biology Department, College of Saint Benedict and Saint John’s University, Collegeville, MN 56321
| | - Patrick M. Sonner
- Neuroscience, Cell Biology, and Physiology Department, Wright State University, Dayton, OH 45435
| |
Collapse
|
22
|
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: 0.3] [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
|
23
|
Parks ST, Taylor C. Development of a Remote, Course-Based Undergraduate Experience to Facilitate In Silico Study of Microbial Metabolic Pathways. JOURNAL OF MICROBIOLOGY & BIOLOGY EDUCATION 2022; 23:jmbe00318-21. [PMID: 35340445 PMCID: PMC8941885 DOI: 10.1128/jmbe.00318-21] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/30/2021] [Accepted: 01/19/2022] [Indexed: 05/09/2023]
Abstract
Course-based undergraduate research experiences (CUREs) often occur in a physical lab space, but they can also be offered remotely while maintaining course expectations and providing opportunity for authentic student engagement in research. Using a novel framework, remote Microbial Ecology CURE students used microbes isolated via antimicrobial-challenged Winogradsky columns to investigate phylogeny and metabolism through a hypothesis-driven meta-analysis (MA). Students used 16S rRNA and key metabolic enzymes to compare phylogeny; enzymes were modeled and evaluated for putative conserved domains, culminating in primer design and analysis. Using in silico tools facilitated student development of bioinformatics skills. The MA was subdivided into discrete sections in order to (i) provide a timeline for students to remain on schedule throughout a remote-learning lab experience, (ii) encourage feedback throughout the project, and (iii) facilitate student understanding of the experimental design. MA deliverables were designed to be specific figures with individual titles, legends, and analyses to enable their feedback for subsequent presentations. The six key formative deliverables included a word cloud (used to develop the works cited list and hypothesis), a 16S rRNA phylogenetic tree, an annotated metabolic pathway and three-dimensional model of the key metabolic enzyme, a phylogenetic tree based on the key metabolic enzyme, design and analysis of a primer set for the key metabolic enzyme, and a summative poster and graphical abstract. The MA project yielded poster presentations at virtual conferences, lab presentations, and written reports. Using the hypothesis-based MA model encouraged an authentic research experience, enabling students to develop, discuss, and progress in meaningful experiments.
Collapse
|
24
|
Emery NC, Crispo E, Supp SR, Farrell KJ, Kerkhoff AJ, Bledsoe EK, O'Donnell KL, McCall AC, Aiello-Lammens ME. Data Science in Undergraduate Life Science Education: A Need for Instructor Skills Training. Bioscience 2021; 71:1274-1287. [PMID: 34867087 PMCID: PMC8634500 DOI: 10.1093/biosci/biab107] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/05/2022] Open
Abstract
There is a clear demand for quantitative literacy in the life sciences, necessitating competent instructors in higher education. However, not all instructors are versed in data science skills or research-based teaching practices. We surveyed biological and environmental science instructors (n = 106) about the teaching of data science in higher education, identifying instructor needs and illuminating barriers to instruction. Our results indicate that instructors use, teach, and view data management, analysis, and visualization as important data science skills. Coding, modeling, and reproducibility were less valued by the instructors, although this differed according to institution type and career stage. The greatest barriers were instructor and student background and space in the curriculum. The instructors were most interested in training on how to teach coding and data analysis. Our study provides an important window into how data science is taught in higher education biology programs and how we can best move forward to empower instructors across disciplines.
Collapse
Affiliation(s)
- Nathan C Emery
- Michigan State University, East Lansing, Michigan, United States
| | - Erika Crispo
- Pace University, New York City, New York, United States
| | | | | | | | - Ellen K Bledsoe
- University of Regina with CIEE's Living Data Project, Regina, Saskatchewan, Canada
| | | | | | - Matthew E Aiello-Lammens
- Environmental Studies and Science Department and director of the Environmental Science Graduate Program at Pace University, New York City, New York, United States
| |
Collapse
|
25
|
Drew JC, Grandgenett N, Dinsdale EA, Vázquez Quiñones LE, Galindo S, Morgan WR, Pauley M, Rosenwald A, Triplett EW, Tapprich W, Kleinschmit AJ. There Is More than Multiple Choice: Crowd-Sourced Assessment Tips for Online, Hybrid, and Face-to-Face Environments. JOURNAL OF MICROBIOLOGY & BIOLOGY EDUCATION 2021; 22:e00205-21. [PMID: 34970386 PMCID: PMC8673258 DOI: 10.1128/jmbe.00205-21] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 02/18/2021] [Accepted: 08/12/2021] [Indexed: 06/14/2023]
Abstract
Developing effective assessments of student learning is a challenging task for faculty and even more difficult for those in emerging disciplines that lack readily available resources and standards. With the power of technology-enhanced education and accessible digital learning platforms, instructors are also looking for assessments that work in an online format. This article will be useful for all teachers, but especially for entry-level instructors, in addition to more mature instructors who are looking to become more well versed in assessment, who seek a succinct summary of assessment types to springboard the integration of new forms of assessment of student learning into their courses. In this paper, ten assessment types, all appropriate for face-to-face, blended, and online modalities, are discussed. The assessments are mapped to a set of bioinformatics core competencies with examples of how they have been used to assess student learning. Although bioinformatics is used as the focus of the assessment types, the question types are relevant to many disciplines.
Collapse
Affiliation(s)
- Jennifer C. Drew
- Department of Microbiology and Cell Science, Institute of Food and Agricultural Sciences, University of Florida, Gainesville, Florida, USA
| | - Neal Grandgenett
- Department of Teacher Education, University of Nebraska at Omaha, Omaha, Nebraska, USA
| | - Elizabeth A. Dinsdale
- College of Science and Engineering, Flinders University, Bedford Park, South Australia, Australia
| | - Luis E. Vázquez Quiñones
- Division of Science and Technology, Universidad Ana G. Méndez–Cupey Campus, San Juan, Puerto Rico
| | - Sebastian Galindo
- Department of Agricultural Education and Communication, Institute of Food and Agricultural Sciences, University of Florida, Gainesville, Florida, USA
| | | | - Mark Pauley
- Division of Undergraduate Education, National Science Foundation, Alexandria, Virginia, USA
| | - Anne Rosenwald
- Department of Biology, Georgetown University, Washington, DC, USA
| | - Eric W. Triplett
- Department of Microbiology and Cell Science, Institute of Food and Agricultural Sciences, University of Florida, Gainesville, Florida, USA
| | - William Tapprich
- Department of Biology, University of Nebraska at Omaha, Omaha, Nebraska, USA
| | - Adam J. Kleinschmit
- Department of Natural and Applied Sciences, University of Dubuque, Dubuque, Iowa, USA
| |
Collapse
|
26
|
Stinziano JR, Roback C, Sargent D, Murphy BK, Hudson PJ, Muir CD. Principles of resilient coding for plant ecophysiologists. AOB PLANTS 2021; 13:plab059. [PMID: 34646435 PMCID: PMC8501907 DOI: 10.1093/aobpla/plab059] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/24/2020] [Accepted: 09/15/2021] [Indexed: 06/02/2023]
Abstract
Plant ecophysiology is founded on a rich body of physical and chemical theory, but it is challenging to connect theory with data in unambiguous, analytically rigorous and reproducible ways. Custom scripts written in computer programming languages (coding) enable plant ecophysiologists to model plant processes and fit models to data reproducibly using advanced statistical techniques. Since many ecophysiologists lack formal programming education, we have yet to adopt a unified set of coding principles and standards that could make coding easier to learn, use and modify. We identify eight principles to help in plant ecophysiologists without much programming experience to write resilient code: (i) standardized nomenclature, (ii) consistency in style, (iii) increased modularity/extensibility for easier editing and understanding, (iv) code scalability for application to large data sets, (v) documented contingencies for code maintenance, (vi) documentation to facilitate user understanding; (vii) extensive tutorials and (viii) unit testing and benchmarking. We illustrate these principles using a new R package, {photosynthesis}, which provides a set of analytical and simulation tools for plant ecophysiology. Our goal with these principles is to advance scientific discovery in plant ecophysiology by making it easier to use code for simulation and data analysis, reproduce results and rapidly incorporate new biological understanding and analytical tools.
Collapse
Affiliation(s)
- Jospeh R Stinziano
- Department of Biology, University of New Mexico, Albuquerque, NM 87131, USA
| | - Cassaundra Roback
- Department of Biology, University of New Mexico, Albuquerque, NM 87131, USA
| | - Demi Sargent
- Hawkesbury Institute for the Environment, Western Sydney University, Sydney 2753, Australia
| | - Bridget K Murphy
- Department of Biology, University of Toronto, Mississauga L5L 1C6, Canada
| | - Patrick J Hudson
- Department of Biology, University of New Mexico, Albuquerque, NM 87131, USA
| | | |
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
|
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
|
29
|
da Silva AL, Abreu APD, Mariano D, Caixeta F, Santos FB, Lage FSD, Quintanilha-Peixoto G, Hilário HO, Xavier JS, Queiroz LR, de Toledo NE, Tavares R, Kato RB, dos Santos RG, Soares S, Goes WM, Nogueira WG, Batista TM, Ortega JM, De Carvalho VAA, Franco GR, Melo-Minardi RCD, Góes-Neto A. From In-Person to the Online World: Insights Into Organizing Events in Bioinformatics. FRONTIERS IN BIOINFORMATICS 2021; 1:711463. [DOI: 10.3389/fbinf.2021.711463] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/18/2021] [Accepted: 08/16/2021] [Indexed: 11/13/2022] Open
Abstract
Bioinformatics is a fast-evolving research field, requiring effective educational initiatives to bring computational knowledge to Life Sciences. Since 2017, an organizing committee composed of graduate students and postdoctoral researchers from the Universidade Federal de Minas Gerais (Brazil) promotes a week-long event named Summer Course in Bioinformatics (CVBioinfo). This event aims to diffuse bioinformatic principles, news, and methods mainly focused on audiences of undergraduate students. Furthermore, as the advent of the COVID-19 global pandemic has precluded in-person events, we offered the event in online mode, using free video transmission platforms. Herein, we present and discuss the insights obtained from promoting the Online Workshop in Bioinformatics (WOB) organized in November 2020, comparing it to our experience in previous in-person editions of the same event.
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: 0.5] [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
|
Zeng H, Zhang J, Preising GA, Rubel T, Singh P, Ritz A. Graphery: interactive tutorials for biological network algorithms. Nucleic Acids Res 2021; 49:W257-W262. [PMID: 34037782 PMCID: PMC8262715 DOI: 10.1093/nar/gkab420] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2021] [Revised: 04/19/2021] [Accepted: 05/03/2021] [Indexed: 11/14/2022] Open
Abstract
Networks have been an excellent framework for modeling complex biological information, but the methodological details of network-based tools are often described for a technical audience. We have developed Graphery, an interactive tutorial webserver that illustrates foundational graph concepts frequently used in network-based methods. Each tutorial describes a graph concept along with executable Python code that can be interactively run on a graph. Users navigate each tutorial using their choice of real-world biological networks that highlight the diverse applications of network algorithms. Graphery also allows users to modify the code within each tutorial or write new programs, which all can be executed without requiring an account. Graphery accepts ideas for new tutorials and datasets that will be shaped by both computational and biological researchers, growing into a community-contributed learning platform. Graphery is available at https://graphery.reedcompbio.org/.
Collapse
Affiliation(s)
- Heyuan Zeng
- Computer Science Department, Reed College, 3203 SE Woodstock Blvd, Portland, OR 97202, USA.,Biology Department, Reed College, 3203 SE Woodstock Blvd, Portland, OR 97202, USA
| | - Jinbiao Zhang
- Information and Communication Technology Department, Xiamen University Malaysia, Jalan Sunsuria, Bandar Sunsuria, 43900 Sepang, Selangor Darul Ehsan, Malaysia
| | - Gabriel A Preising
- Biology Department, Reed College, 3203 SE Woodstock Blvd, Portland, OR 97202, USA
| | - Tobias Rubel
- Biology Department, Reed College, 3203 SE Woodstock Blvd, Portland, OR 97202, USA
| | - Pramesh Singh
- Biology Department, Reed College, 3203 SE Woodstock Blvd, Portland, OR 97202, USA
| | - Anna Ritz
- Biology Department, Reed College, 3203 SE Woodstock Blvd, Portland, OR 97202, USA
| |
Collapse
|
32
|
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
|
33
|
Goller CC, Srougi MC, Chen SH, Schenkman LR, Kelly RM. Integrating Bioinformatics Tools Into Inquiry-Based Molecular Biology Laboratory Education Modules. FRONTIERS IN EDUCATION 2021; 6:711403. [PMID: 35036827 PMCID: PMC8758113 DOI: 10.3389/feduc.2021.711403] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
The accelerating expansion of online bioinformatics tools has profoundly impacted molecular biology, with such tools becoming integral to the modern life sciences. As a result, molecular biology laboratory education must train students to leverage bioinformatics in meaningful ways to be prepared for a spectrum of careers. Institutions of higher learning can benefit from a flexible and dynamic instructional paradigm that blends up-to-date bioinformatics training with best practices in molecular biology laboratory pedagogy. At North Carolina State University, the campus-wide interdisciplinary Biotechnology (BIT) Program has developed cutting-edge, flexible, inquiry-based Molecular Biology Laboratory Education Modules (MBLEMs). MBLEMs incorporate relevant online bioinformatics tools using evidenced-based pedagogical practices and in alignment with national learning frameworks. Students in MBLEMs engage in the most recent experimental developments in modern biology (e.g., CRISPR, metagenomics) through the strategic use of bioinformatics, in combination with wet-lab experiments, to address research questions. MBLEMs are flexible educational units that provide a menu of inquiry-based laboratory exercises that can be used as complete courses or as parts of existing courses. As such, MBLEMs are designed to serve as resources for institutions ranging from community colleges to research-intensive universities, involving a diverse range of learners. Herein, we describe this new paradigm for biology laboratory education that embraces bioinformatics as a critical component of inquiry-based learning for undergraduate and graduate students representing the life sciences, the physical sciences, and engineering.
Collapse
Affiliation(s)
- Carlos C. Goller
- Biotechnology (BIT) Program, North Carolina State University, Raleigh, NC, United States
- Department of Biological Sciences, College of Sciences, North Carolina State University, Raleigh, NC, United States
| | - Melissa C. Srougi
- Biotechnology (BIT) Program, North Carolina State University, Raleigh, NC, United States
- Department of Molecular Biomedical Sciences, College of Veterinary Medicine, North Carolina State University, Raleigh, NC, United States
| | - Stefanie H. Chen
- Biotechnology (BIT) Program, North Carolina State University, Raleigh, NC, United States
- Department of Biological Sciences, College of Sciences, North Carolina State University, Raleigh, NC, United States
| | - Laura R. Schenkman
- Biotechnology (BIT) Program, North Carolina State University, Raleigh, NC, United States
| | - Robert M. Kelly
- Biotechnology (BIT) Program, North Carolina State University, Raleigh, NC, United States
- Department of Chemical and Biomolecular Engineering, North Carolina State University, Raleigh, NC, United States
| |
Collapse
|
34
|
Niepielko MG, Shumskaya M. Early Requirement for Bioinformatics in Undergraduate Biology Curricula. FRONTIERS IN BIOINFORMATICS 2021; 1:656531. [PMID: 36303737 PMCID: PMC9581004 DOI: 10.3389/fbinf.2021.656531] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2021] [Accepted: 04/08/2021] [Indexed: 11/13/2022] Open
Affiliation(s)
- Matthew G. Niepielko
- New Jersey Center for Science, Technology, and Mathematics, Kean University, Union, NJ, United States
| | - Maria Shumskaya
- School of Natural Sciences, Biology, Kean University, Union, NJ, United States
- *Correspondence: Maria Shumskaya,
| |
Collapse
|
35
|
Robinson SL, Biernath T, Rosenthal C, Young D, Wackett LP, Martinez-Vaz BM. Development of the Organonitrogen Biodegradation Database: Teaching Bioinformatics and Collaborative Skills to Undergraduates during a Pandemic. JOURNAL OF MICROBIOLOGY & BIOLOGY EDUCATION 2021; 22:jmbe-22-49. [PMID: 33884084 PMCID: PMC8046652 DOI: 10.1128/jmbe.v22i1.2351] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 09/29/2020] [Accepted: 12/09/2020] [Indexed: 05/24/2023]
Abstract
Physical distancing and inaccessibility to laboratory facilities created an opportunity to transition undergraduate research experiences to remote, digital platforms, adding another level of pedagogy to their training. Basic bioinformatics skills together with critical analysis of scientific literature are essential for addressing research questions in modern biology. The work presented here describes a fully online, collaborative research experience created to allow undergraduate students to learn those skills. The research experience was focused on the development and implementation of the Organonitrogen Biodegradation Database (ONDB, z.umn.edu/ondb). The ONDB was developed to catalog information about the cost, chemical properties, and biodegradation potential of commonly used organonitrogen compounds. A cross-institutional team of undergraduate researchers worked in collaboration with two faculty members and a postdoctoral fellow to develop the database. Students carried out extensive online literature searches and used a biodegradation prediction website to research and represent the microbial catabolism of different organonitrogen compounds. Participants employed computational tools such as R, Shiny, and flexdashboard to construct the database pages and interactive web interface for the ONDB. Worksheets and forms were created to encourage other students and researchers to gather information about organonitrogen compounds and expand the database. Student progress was evaluated through biweekly project meetings, presentations, and a final reflection. The ONDB undergraduate research experience provided a platform for students to learn bioinformatics skills while simultaneously developing a teaching and research tool for others.
Collapse
Affiliation(s)
| | - Troy Biernath
- Department of Chemistry and Biochemistry Program, Bethel University, Saint Paul, MN 55112, USA
| | - Caleb Rosenthal
- Department of Biology and Biochemistry Program, Hamline University, Saint Paul, MN 55104, USA
| | - Dean Young
- Department of Biology and Biochemistry Program, Hamline University, Saint Paul, MN 55104, USA
| | - Lawrence P. Wackett
- Department of Biochemistry, Molecular Biology and Biophysics and Biotechnology Institute, University of Minnesota, Saint Paul, MN 55108, USA
| | - Betsy M. Martinez-Vaz
- Department of Biology and Biochemistry Program, Hamline University, Saint Paul, MN 55104, USA
| |
Collapse
|
36
|
Petrie KL, Xie R. Resequencing of Microbial Isolates: A Lab Module to Introduce Novices to Command-Line Bioinformatics. Front Microbiol 2021; 12:578859. [PMID: 33796082 PMCID: PMC8008064 DOI: 10.3389/fmicb.2021.578859] [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: 07/01/2020] [Accepted: 02/16/2021] [Indexed: 11/23/2022] Open
Abstract
Familiarity with genome-scale data and the bioinformatic skills to analyze it have become essential for understanding and advancing modern biology and human health, yet many undergraduate biology majors are never exposed to hands-on bioinformatics. This paper presents a module that introduces students to applied bioinformatic analysis within the context of a research-based microbiology lab course. One of the most commonly used genomic analyses in biology is resequencing: determining the sequence of DNA bases in a derived strain of some organism, and comparing it to the known ancestral genome of that organism to better understand the phenotypic differences between them. Many existing CUREs - Course Based Undergraduate Research Experiences - evolve or select new strains of bacteria and compare them phenotypically to ancestral strains. This paper covers standardized strategies and procedures, accessible to undergraduates, for preparing and analyzing microbial whole-genome resequencing data to examine the genotypic differences between such strains. Wet-lab protocols and computational tutorials are provided, along with additional guidelines for educators, providing instructors without a next-generation sequencing or bioinformatics background the necessary information to incorporate whole-genome sequencing and command-line analysis into their class. This module introduces novice students to running software at the command-line, giving them exposure and familiarity with the types of tools that make up the vast majority of open-source scientific software used in contemporary biology. Completion of the module improves student attitudes toward computing, which may make them more likely to pursue further bioinformatics study.
Collapse
Affiliation(s)
- Katherine Lynn Petrie
- Division of Biological Sciences, University of California, San Diego, La Jolla, CA, United States
- Earth-Life Science Institute, Tokyo Institute of Technology, Tokyo, Japan
| | - Rujia Xie
- Division of Biological Sciences, University of California, San Diego, La Jolla, CA, United States
| |
Collapse
|
37
|
Tapprich WE, Reichart L, Simon DM, Duncan G, McClung W, Grandgenett N, Pauley MA. An instructional definition and assessment rubric for bioinformatics instruction. BIOCHEMISTRY AND MOLECULAR BIOLOGY EDUCATION : A BIMONTHLY PUBLICATION OF THE INTERNATIONAL UNION OF BIOCHEMISTRY AND MOLECULAR BIOLOGY 2021; 49:38-45. [PMID: 32744803 DOI: 10.1002/bmb.21361] [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: 01/31/2019] [Revised: 02/06/2020] [Accepted: 04/20/2020] [Indexed: 06/11/2023]
Abstract
The lack of an instructional definition of bioinformatics delays its effective integration into biology coursework. Using an iterative process, our team of biologists, a mathematician/computer scientist, and a bioinformatician together with an educational evaluation and assessment specialist, developed an instructional definition of the discipline: Bioinformatics is "an interdisciplinary field that is concerned with the development and application of algorithms that analyze biological data to investigate the structure and function of biological polymers and their relationships to living systems." The field is defined in terms of its two primary foundational disciplines, biology and computer science, and its interdisciplinary nature. At the same time, we also created a rubric for assessing open-ended responses to a prompt about what bioinformatics is and how it is used. The rubric has been shown to be reliable in successive rounds of testing using both common percent agreement (89.7%) and intraclass correlation coefficient (0.620) calculations. We offer the definition and rubric to life sciences instructors to help further integrate bioinformatics into biology instruction, as well as for fostering further educational research projects.
Collapse
Affiliation(s)
- William E Tapprich
- Department of Biology, University of Nebraska at Omaha, Omaha, Nebraska, USA
| | - Letitia Reichart
- Department of Biology, University of Nebraska at Kearney, Kearney, Nebraska, USA
| | - Dawn M Simon
- Department of Biology, University of Nebraska at Kearney, Kearney, Nebraska, USA
| | - Garry Duncan
- Biology Department, Nebraska Wesleyan University, Lincoln, Nebraska, USA
| | - William McClung
- Mathematics and Computer Science Department, Nebraska Wesleyan University, Lincoln, Nebraska, USA
| | - Neal Grandgenett
- Department of Teacher Education, University of Nebraska at Omaha, Omaha, Nebraska, USA
| | - Mark A Pauley
- School of Interdisciplinary Informatics, University of Nebraska at Omaha, Omaha, Nebraska, USA
| |
Collapse
|
38
|
Lyles JK, Oli M. The student-centered classroom: the new gut feeling. FEMS Microbiol Lett 2020; 367:6000213. [PMID: 33232449 DOI: 10.1093/femsle/fnaa191] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2020] [Accepted: 11/17/2020] [Indexed: 12/19/2022] Open
Abstract
A student-centered, interactive course-based undergraduate research experience (CURE) was implemented in a microbiology course in order to provide an authentic research experience and to stimulate student interest and improve understanding of fermentation, probiotics, the human microbiome and related topics. Students were immersed in the scientific process as they used fundamental techniques to investigate the probiotic composition of a fermented milk beverage, kefir-an unknown question with no predetermined outcomes. In order to assess the benefits and effect of this learning experience on the students, pre- and post-study surveys were administered using Qualtrics. Post-study, 93% of participants agreed that fermented foods are beneficial to human health (compared to 52% pre-study), and notably, 100% of participants indicated that they plan to apply this material in both their personal and professional lives and would suggest consuming probiotics or fermented products to alleviate gastrointestinal issues. As evidenced by demographic data, this CURE is suitable for implementation at both large and small institutions with diverse student populations. Collectively, these data indicate that this collaborative, discovery-based learning experience is a powerful educational tool, encouraging students to make real-life connections between microbiology, medicine and their own health.
Collapse
Affiliation(s)
- Jennifer K Lyles
- Department of Biology, Francis Marion University, P.O. Box 100547, Florence, SC 29502, USA
| | - Monika Oli
- Department of Microbiology and Cell Science, University of Florida, PO Box 110700, Gainesville, FL 32611, USA
| |
Collapse
|
39
|
Clemmons AW, Timbrook J, Herron JC, Crowe AJ. BioSkills Guide: Development and National Validation of a Tool for Interpreting the Vision and Change Core Competencies. CBE LIFE SCIENCES EDUCATION 2020; 19:ar53. [PMID: 33001766 PMCID: PMC8693931 DOI: 10.1187/cbe.19-11-0259] [Citation(s) in RCA: 48] [Impact Index Per Article: 9.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/13/2019] [Revised: 08/11/2020] [Accepted: 08/15/2020] [Indexed: 05/24/2023]
Abstract
To excel in modern science, technology, engineering, and mathematics careers, biology majors need a range of transferable skills, yet competency development is often a relatively underdeveloped facet of the undergraduate curriculum. We have elaborated the Vision and Change core competency framework into a resource called the BioSkills Guide, a set of measurable learning outcomes that can be more readily implemented by faculty. Following an iterative review process including more than 200 educators, we gathered evidence of the BioSkills Guide's content validity using a national survey of more than 400 educators. Rates of respondent support were high (74.3-99.6%) across the 77 outcomes in the final draft. Our national sample during the development and validation phases included college biology educators representing more than 250 institutions, including 73 community colleges, and a range of course levels and biology subdisciplines. Comparison of the BioSkills Guide with other science competency frameworks reveals significant overlap but some gaps and ambiguities. These differences may reflect areas where understandings of competencies are still evolving in the undergraduate biology community, warranting future research. We envision the BioSkills Guide supporting a variety of applications in undergraduate biology, including backward design of individual lessons and courses, competency assessment development, and curriculum mapping and planning.
Collapse
Affiliation(s)
| | - Jerry Timbrook
- Department of Sociology, University of Nebraska–Lincoln, Lincoln, NE 68588
| | - Jon C. Herron
- Department of Biology, University of Washington, Seattle, WA 98195
| | - Alison J. Crowe
- Department of Biology, University of Washington, Seattle, WA 98195
| |
Collapse
|
40
|
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
|
41
|
Rosen GL, Hammrich P. Teaching Microbiome Analysis: From Design to Computation Through Inquiry. Front Microbiol 2020; 11:528051. [PMID: 33193120 PMCID: PMC7658192 DOI: 10.3389/fmicb.2020.528051] [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: 01/18/2020] [Accepted: 09/09/2020] [Indexed: 11/23/2022] Open
Abstract
In this article, we present our three-class course sequence to educate students about microbiome analysis and metagenomics through experiential learning by taking them from inquiry to analysis of the microbiome: Molecular Ecology Lab, Bioinformatics, and Computational Microbiome Analysis. Students developed hypotheses, designed lab experiments, sequenced the DNA from microbiomes, learned basic python/R scripting, became proficient in at least one microbiome analysis software, and were able to analyze data generated from the microbiome experiments. While over 150 students (graduate and undergraduate) were impacted by the development of the series of courses, our assessment was only on undergraduate learning, where 45 students enrolled in at least one of the three courses and 4 students took all three. Students gained skills in bioinformatics through the courses, and several positive comments were received through surveys and private correspondence. Through a summative assessment, general trends show that students became more proficient in comparative genomic techniques and had positive attitudes toward their abilities to bridge biology and bioinformatics. While most students took individual or 2 of the courses, we show that pre- and post-surveys of these individual classes still showed progress toward learning objectives. It is expected that students trained will enter the workforce with skills needed to innovate in the biotechnology, health, and environmental industries. Students are trained to maximize impact and tackle real world problems in biology and medicine with their learned knowledge of data science and machine learning. The course materials for the new microbiome analysis course are available on Github: https://github.com/EESI/Comp_Metagenomics_resources.
Collapse
Affiliation(s)
- Gail L. Rosen
- Ecological and Evolutionary Signal-processing and Informatics (EESI) Laboratory, Electrical and Computer Engineering, Drexel University, Philadelphia, PA, United States
| | - Penny Hammrich
- School of Education, Drexel University, Philadelphia, PA, United States
| |
Collapse
|
42
|
Mitchell K, Ronas J, Dao C, Freise AC, Mangul S, Shapiro C, Moberg Parker J. PUMAA: A Platform for Accessible Microbiome Analysis in the Undergraduate Classroom. Front Microbiol 2020; 11:584699. [PMID: 33123113 PMCID: PMC7573227 DOI: 10.3389/fmicb.2020.584699] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2020] [Accepted: 09/14/2020] [Indexed: 12/22/2022] Open
Abstract
Improvements in high-throughput sequencing makes targeted amplicon analysis an ideal method for the study of human and environmental microbiomes by undergraduates. Multiple bioinformatics programs are available to process and interpret raw microbial diversity datasets, and the choice of programs to use in curricula is largely determined by student learning goals. Many of the most commonly used microbiome bioinformatics platforms offer end-to-end data processing and data analysis using a command line interface (CLI), but the downside for novice microbiome researchers is the steep learning curve often required. Alternatively, some sequencing providers include processing of raw data and taxonomy assignments as part of their pipelines. This, when coupled with available web-based or graphical user interface (GUI) analysis and visualization tools, eliminates the need for students or instructors to have extensive CLI experience. However, lack of universal data formats can make integration of these tools challenging. For example, tools for upstream and downstream analyses frequently use multiple different data formats which then require writing custom scripts or hours of manual work to make the files compatible. Here, we describe a microbial ecology bioinformatics curriculum that focuses on data analysis, visualization, and statistical reasoning by taking advantage of existing web-based and GUI tools. We created the Program for Unifying Microbiome Analysis Applications (PUMAA), which solves the problem of inconsistent files by formatting the output files from several raw data processing programs to seamlessly transition to a suite of GUI programs for analysis and visualization of microbiome taxonomic and inferred functional profiles. Additionally, we created a series of tutorials to accompany each of the microbiome analysis curricular modules. From pre- and post-course surveys, students in this curriculum self-reported conceptual and confidence gains in bioinformatics and data analysis skills. Students also demonstrated gains in biologically relevant statistical reasoning based on rubric-guided evaluations of open-ended survey questions and the Statistical Reasoning in Biology Concept Inventory. The PUMAA program and associated analysis tutorials enable students and researchers with no computational experience to effectively analyze real microbiome datasets to investigate real-world research questions.
Collapse
Affiliation(s)
- Keith Mitchell
- Department of Microbiology, Immunology and Molecular Genetics, University of California, Los Angeles, Los Angeles, CA, United States
| | - Jiem Ronas
- Department of Microbiology, Immunology and Molecular Genetics, University of California, Los Angeles, Los Angeles, CA, United States
| | - Christopher Dao
- Department of Microbiology, Immunology and Molecular Genetics, University of California, Los Angeles, Los Angeles, CA, United States
| | - Amanda C Freise
- Department of Microbiology, Immunology and Molecular Genetics, University of California, Los Angeles, Los Angeles, CA, United States
| | - Serghei Mangul
- Department of Clinical Pharmacy, School of Pharmacy, University of Southern California, Los Angeles, CA, United States
| | - Casey Shapiro
- Center for Educational Assessment, Center for the Advancement of Teaching, University of California, Los Angeles, Los Angeles, CA, United States
| | - Jordan Moberg Parker
- Department of Microbiology, Immunology and Molecular Genetics, University of California, Los Angeles, Los Angeles, CA, United States
| |
Collapse
|
43
|
Martinez-Vaz BM, Mickelson MM. In silico Phage Hunting: Bioinformatics Exercises to Identify and Explore Bacteriophage Genomes. Front Microbiol 2020; 11:577634. [PMID: 33072043 PMCID: PMC7533560 DOI: 10.3389/fmicb.2020.577634] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2020] [Accepted: 08/26/2020] [Indexed: 12/24/2022] Open
Abstract
Bioinformatics skills are increasingly relevant to research in most areas of the life sciences. The availability of genome sequences and large data sets provide unique opportunities to incorporate bioinformatics exercises into undergraduate microbiology courses. The goal of this project was to develop a teaching module to investigate the abundance and phylogenetic relationships amongst bacteriophages using a set of freely available bioinformatics tools. Computational identification and examination of bacteriophage genomes, followed by phylogenetic analyses, provides opportunities to incorporate core bioinformatics competencies in microbiology courses and enhance students' bioinformatics skills. The first activity consisted of using PHASTER (PHAge Search Tool Enhanced Release), a bioinformatics tool that identifies bacteriophage sequences within bacterial chromosomes. Further computational analyses were conducted to align bacteriophage proteins, genomes, and determine phylogenetic relationships amongst these viruses. This part of the project was carried out using the Clustal omega, MAFFT (Multiple Alignment using Fast Fourier Transform), and Interactive Tree of Life (iTOL) programs for sequence alignments and phylogenetic analyses. The laboratory activities were field tested in undergraduate directed research, and microbiology classes. The learning objectives were assessed by comparing the scores of pre and post-tests and grading final presentations. Post-tests were higher than pre-test scores at or below p = 0.002. The data suggest in silico phage hunting improves students' ability to search databases, interpret phylogenetic trees, and use bioinformatics tools to examine genome structure. This activity allows instructors to integrate key bioinformatic concepts in their curriculums and gives students the opportunity to participate in a research-directed learning environment in the classroom.
Collapse
|
44
|
Kruchten AE. A Curricular Bioinformatics Approach to Teaching Undergraduates to Analyze Metagenomic Datasets Using R. Front Microbiol 2020; 11:578600. [PMID: 33013816 PMCID: PMC7511545 DOI: 10.3389/fmicb.2020.578600] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2020] [Accepted: 08/12/2020] [Indexed: 01/06/2023] Open
Abstract
Biologists with bioinformatic skills will be better prepared for the job market, but relatively few biology programs require bioinformatics courses. Inclusion in the curriculum may be hindered by several barriers, including lack of faculty expertise, student resistance to computational work, and few examples in the pedagogical literature. An 8-week wet-lab and in silico research experience for undergraduates was implemented. Students performed DNA purification and metagenomics analysis to compare the diversity and abundance of microbes in two samples. Students sampled snow from sites in northern Minnesota and purified genomic DNA from the microbes, followed by metagenomic analysis. Students used an existing metagenomic dataset to practice analysis skills, including comparing the use of Excel versus R for analysis and visualization of a large dataset. Upon receipt of the snow data, students applied their recently acquired skills to their new dataset and reported their results via a poster. Several outcomes were achieved as a result of this module. First, YouTube videos demonstrating hands-on metagenomics and R techniques were used as professional development for faculty, leading to broadened research capabilities and comfort with bioinformatics. Second, students were introduced to computational skills in a manner that was intentional, with time for both introduction and reinforcement of skills. Finally, the module was effectively included in a biology curriculum because it could function as either a stand-alone course or a module within another course such as microbiology. This module, developed with Course-based Undergraduate Research Experience guidelines in mind, introduces students and faculty to bioinformatics in biology research.
Collapse
Affiliation(s)
- Anne E Kruchten
- Department of Biology, The College of St. Scholastica, Duluth, MN, United States
| |
Collapse
|
45
|
Davies A, Mueller J, Moulton G. Core competencies for clinical informaticians: A systematic review. Int J Med Inform 2020; 141:104237. [PMID: 32771960 DOI: 10.1016/j.ijmedinf.2020.104237] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2020] [Revised: 07/20/2020] [Accepted: 07/21/2020] [Indexed: 12/20/2022]
Abstract
BACKGROUND Building on initial work carried out by the Faculty of Clinical Informatics (FCI) in the UK, the creation of a national competency framework for Clinical Informatics is required for the definition of clinical informaticians' professional attributes and skills. We aimed to systematically review the academic literature relating to competencies, skills and existing course curricula in the clinical and health related informatics domains. METHODS Two independent reviewers searched Web of Science, EMBASE, ERIC, PubMed and CINAHL. Publications were included if they reported details of relevant competencies, skills and existing course curricula. We report findings using the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) statement. RESULTS A total of 82 publications were included. The most frequently used method was surveys (30 %) followed by narrative descriptions (28 %). Most of the publications describe curriculum design (23 %) followed by competency definition (18 %) and skills, qualifications & training (18 %). Core skills surrounding data, information systems and information management appear to be cross-cutting across the various informatics disciplines with Bioinformatics and Pharmacy Informatics expressing the most unique competency requirements. CONCLUSION We identified eight key domains that cut across the different sub-disciplines of health informatics, including data, information management, human factors, project management, research skills/knowledge, leadership and management, systems development and evaluation, and health/healthcare. Some informatics disciplines such as Nursing Informatics appear to be further ahead at achieving widespread competency standardisation. Attempts at standardisation for competencies should be tempered with flexibility to allow for local variation and requirements.
Collapse
Affiliation(s)
- Alan Davies
- School of Health Sciences, University of Manchester, Manchester, United Kingdom.
| | - Julia Mueller
- MRC Epidemiology Unit, University of Cambridge, Cambridge, United Kingdom
| | - Georgina Moulton
- School of Health Sciences, University of Manchester, Manchester, United Kingdom; Health Data Research United Kingdom (HDRUK), London, United Kingdom
| |
Collapse
|
46
|
Bennett JA. The CURE for the Typical Bioinformatics Classroom. Front Microbiol 2020; 11:1728. [PMID: 32903295 PMCID: PMC7434937 DOI: 10.3389/fmicb.2020.01728] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2020] [Accepted: 07/02/2020] [Indexed: 11/19/2022] Open
Affiliation(s)
- Jennifer A. Bennett
- Department of Biology and Earth Science, Otterbein University, Westerville, OH, United States
- Biochemistry and Molecular Biology Program, Otterbein University, Westerville, OH, United States
- *Correspondence: Jennifer A. Bennett
| |
Collapse
|
47
|
Ryder EF, Morgan WR, Sierk M, Donovan SS, Robertson SD, Orndorf HC, Rosenwald AG, Triplett EW, Dinsdale E, Pauley MA, Tapprich WE. Incubators: Building community networks and developing open educational resources to integrate bioinformatics into life science education. BIOCHEMISTRY AND MOLECULAR BIOLOGY EDUCATION : A BIMONTHLY PUBLICATION OF THE INTERNATIONAL UNION OF BIOCHEMISTRY AND MOLECULAR BIOLOGY 2020; 48:381-390. [PMID: 32585745 PMCID: PMC7496352 DOI: 10.1002/bmb.21387] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/23/2019] [Revised: 05/02/2020] [Accepted: 05/18/2020] [Indexed: 06/11/2023]
Abstract
While it is essential for life science students to be trained in modern techniques and approaches, rapidly developing, interdisciplinary fields such as bioinformatics present distinct challenges to undergraduate educators. In particular, many educators lack training in new fields, and high-quality teaching and learning materials may be sparse. To address this challenge with respect to bioinformatics, the Network for the Integration of Bioinformatics into Life Science Education (NIBLSE), in partnership with Quantitative Undergraduate Biology Education and Synthesis (QUBES), developed incubators, a novel collaborative process for the development of open educational resources (OER). Incubators are short-term, online communities that refine unpublished teaching lessons into more polished and widely usable learning resources. The resulting products are published and made freely available in the NIBLSE Resource Collection, providing recognition of scholarly work by incubator participants. In addition to producing accessible, high-quality resources, incubators also provide opportunities for faculty development. Because participants are intentionally chosen to represent a range of expertise in bioinformatics and pedagogy, incubators also build professional connections among educators with diverse backgrounds and perspectives and promote the discussion of practical issues involved in deploying a resource in the classroom. Here we describe the incubator process and provide examples of beneficial outcomes. Our experience indicates that incubators are a low cost, short-term, flexible method for the development of OERs and professional community that could be adapted to a variety of disciplinary and pedagogical contexts.
Collapse
Affiliation(s)
- Elizabeth F. Ryder
- Department of Biology and BiotechnologyWorcester Polytechnic InstituteWorcesterMassachusettsUSA
| | | | - Michael Sierk
- Interdisciplinary Science DepartmentSaint Vincent CollegeLatrobePennsylvaniaUSA
| | - Samuel S. Donovan
- Department of Biological SciencesUniversity of PittsburghPittsburghPennsylvaniaUSA
| | - Sabrina D. Robertson
- Department of Psychology and NeuroscienceUniversity of North CarolinaChapel HillNorth CarolinaUSA
| | - Hayley C. Orndorf
- Department of Biological SciencesUniversity of PittsburghPittsburghPennsylvaniaUSA
| | - Anne G. Rosenwald
- Department of BiologyGeorgetown UniversityWashingtonDistrict of ColumbiaUSA
| | - Eric W. Triplett
- Microbiology and Cell Science DepartmentUniversity of FloridaGainesvilleFloridaUSA
| | | | - Mark A. Pauley
- Division of Undergraduate Education, Directorate for Education and Human ResourcesNational Science FoundationAlexandriaVirginiaUSA
| | | |
Collapse
|
48
|
Tractenberg RE, Lindvall JM, Attwood TK, Via A. The Mastery Rubric for Bioinformatics: A tool to support design and evaluation of career-spanning education and training. PLoS One 2019; 14:e0225256. [PMID: 31770418 PMCID: PMC6879125 DOI: 10.1371/journal.pone.0225256] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2019] [Accepted: 10/24/2019] [Indexed: 11/18/2022] Open
Abstract
As the life sciences have become more data intensive, the pressure to incorporate the requisite training into life-science education and training programs has increased. To facilitate curriculum development, various sets of (bio)informatics competencies have been articulated; however, these have proved difficult to implement in practice. Addressing this issue, we have created a curriculum-design and -evaluation tool to support the development of specific Knowledge, Skills and Abilities (KSAs) that reflect the scientific method and promote both bioinformatics practice and the achievement of competencies. Twelve KSAs were extracted via formal analysis, and stages along a developmental trajectory, from uninitiated student to independent practitioner, were identified. Demonstration of each KSA by a performer at each stage was initially described (Performance Level Descriptors, PLDs), evaluated, and revised at an international workshop. This work was subsequently extended and further refined to yield the Mastery Rubric for Bioinformatics (MR-Bi). The MR-Bi was validated by demonstrating alignment between the KSAs and competencies, and its consistency with principles of adult learning. The MR-Bi tool provides a formal framework to support curriculum building, training, and self-directed learning. It prioritizes the development of independence and scientific reasoning, and is structured to allow individuals (regardless of career stage, disciplinary background, or skill level) to locate themselves within the framework. The KSAs and their PLDs promote scientific problem formulation and problem solving, lending the MR-Bi durability and flexibility. With its explicit developmental trajectory, the tool can be used by developing or practicing scientists to direct their (and their team's) acquisition of new, or to deepen existing, bioinformatics KSAs. The MR-Bi is a tool that can contribute to the cultivation of a next generation of bioinformaticians who are able to design reproducible and rigorous research, and to critically analyze results from their own, and others', work.
Collapse
Affiliation(s)
- Rochelle E. Tractenberg
- Collaborative for Research on Outcomes and –Metrics, and Departments of Neurology, Biostatistics, Biomathematics and Bioinformatics, and Rehabilitation Medicine, Georgetown University, Washington, DC, United States of America
| | - Jessica M. Lindvall
- National Bioinformatics Infrastructure Sweden (NBIS)/ELIXIR-SE, Science for Life Laboratory (SciLifeLab), Department of Biochemistry and Biophysics, Stockholm University, Stockholm, Sweden
| | - Teresa K. Attwood
- Department of Computer Science, The University of Manchester, Manchester, England, United Kingdom; The GOBLET Foundation, Radboud University, Nijmegen Medical Centre, Nijmegen, The Netherlands
| | - Allegra Via
- ELIXIR Italy, National Research Council of Italy, Institute of Molecular Biology and Pathology, Rome, Italy
| |
Collapse
|
49
|
Williams JJ, Drew JC, Galindo-Gonzalez S, Robic S, Dinsdale E, Morgan WR, Triplett EW, Burnette JM, Donovan SS, Fowlks ER, Goodman AL, Grandgenett NF, Goller CC, Hauser C, Jungck JR, Newman JD, Pearson WR, Ryder EF, Sierk M, Smith TM, Tosado-Acevedo R, Tapprich W, Tobin TC, Toro-Martínez A, Welch LR, Wilson MA, Ebenbach D, McWilliams M, Rosenwald AG, Pauley MA. Barriers to integration of bioinformatics into undergraduate life sciences education: A national study of US life sciences faculty uncover significant barriers to integrating bioinformatics into undergraduate instruction. PLoS One 2019; 14:e0224288. [PMID: 31738797 PMCID: PMC6860448 DOI: 10.1371/journal.pone.0224288] [Citation(s) in RCA: 27] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2019] [Accepted: 10/09/2019] [Indexed: 01/27/2023] Open
Abstract
Bioinformatics, a discipline that combines aspects of biology, statistics, mathematics, and computer science, is becoming increasingly important for biological research. However, bioinformatics instruction is not yet generally integrated into undergraduate life sciences curricula. To understand why we studied how bioinformatics is being included in biology education in the US by conducting a nationwide survey of faculty at two- and four-year institutions. The survey asked several open-ended questions that probed barriers to integration, the answers to which were analyzed using a mixed-methods approach. The barrier most frequently reported by the 1,260 respondents was lack of faculty expertise/training, but other deterrents—lack of student interest, overly-full curricula, and lack of student preparation—were also common. Interestingly, the barriers faculty face depended strongly on whether they are members of an underrepresented group and on the Carnegie Classification of their home institution. We were surprised to discover that the cohort of faculty who were awarded their terminal degree most recently reported the most preparation in bioinformatics but teach it at the lowest rate.
Collapse
Affiliation(s)
- Jason J. Williams
- Cold Spring Harbor Laboratory, Cold Spring Harbor, NY, United States of America
| | - Jennifer C. Drew
- Microbiology and Cell Science Department, University of Florida, Gainesville, FL, United States of America
| | - Sebastian Galindo-Gonzalez
- Department of Agricultural Education and Communication, University of Florida, Gainesville, FL, United States of America
| | - Srebrenka Robic
- Department of Biology, Agnes Scott College, Decatur, GA, United States of America
| | - Elizabeth Dinsdale
- Department of Biology, San Diego State University, San Diego, CA, United States of America
| | - William R. Morgan
- Department of Biology, College of Wooster, Wooster, OH, United States of America
| | - Eric W. Triplett
- Microbiology and Cell Science Department, University of Florida, Gainesville, FL, United States of America
| | - James M. Burnette
- University of California, Riverside, Riverside, CA, United States of America
| | - Samuel S. Donovan
- Department of Biological Sciences, University of Pittsburgh, Pittsburgh, PA, United States of America
| | - Edison R. Fowlks
- Department of Biological Sciences, Hampton University, Hampton, VA, United States of America
| | - Anya L. Goodman
- Department of Chemistry and Biochemistry, California Polytechnic State University, San Luis Obispo, CA, United States of America
| | - Nealy F. Grandgenett
- Department of Teacher Education, University of Nebraska at Omaha, Omaha, NE, United States of America
| | - Carlos C. Goller
- Department of Biological Sciences, North Carolina State University, Raleigh, NC, United States of America
| | - Charles Hauser
- Department of Biological Sciences, Bioinformatics Program, St. Edward’s University, Austin, TX, United States of America
| | - John R. Jungck
- Departments of Biological Sciences and Mathematical Sciences, University of Delaware, Newark, DE, United States of America
| | - Jeffrey D. Newman
- Department of Biology, Lycoming College, Williamsport, PA, United States of America
| | - William R. Pearson
- Department of Biochemistry and Molecular Genetics, University of Virginia School of Medicine, Charlottesville, VA, United States of America
| | - Elizabeth F. Ryder
- Biology and Biotechnology Department, Worcester Polytechnic Institute, Worcester, MA, United States of America
| | - Michael Sierk
- Bioinformatics Program, Saint Vincent College, Latrobe, PA, United States of America
| | - Todd M. Smith
- Digital World Biology, PMB, Seattle, WA, United States of America
| | - Rafael Tosado-Acevedo
- Department of Natural Sciences, Inter American University of Puerto Rico, Metropolitan Campus, San Juan, PR, United States of America
| | - William Tapprich
- Department of Biology, University of Nebraska at Omaha, Omaha, NE, United States of America
| | - Tammy C. Tobin
- Department of Biology, Susquehanna University, Selinsgrove, PA, United States of America
| | - Arlín Toro-Martínez
- Department of Biology, Chemistry, and Environmental Sciences, Inter American University of Puerto Rico, San Germán Campus, San Germán, PR, United States of America
| | - Lonnie R. Welch
- Department of Computer Science, Ohio University, Athens, OH, United States of America
| | - Melissa A. Wilson
- School of Life Sciences, Arizona State University, Tempe, AZ, United States of America
| | - David Ebenbach
- Center for New Designs in Learning and Scholarship, Georgetown University, Washington, DC, United States of America
| | - Mindy McWilliams
- Center for New Designs in Learning and Scholarship, Georgetown University, Washington, DC, United States of America
| | - Anne G. Rosenwald
- Department of Biology, Georgetown University, Washington, DC, United States of America
| | - Mark A. Pauley
- School of Interdisciplinary Informatics, University of Nebraska at Omaha, Omaha, NE, United States of America
- * E-mail:
| |
Collapse
|
50
|
Wright AM, Schwartz RS, Oaks JR, Newman CE, Flanagan SP. The why, when, and how of computing in biology classrooms. F1000Res 2019; 8:1854. [PMID: 32025290 PMCID: PMC6971840 DOI: 10.12688/f1000research.20873.1] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 10/18/2019] [Indexed: 03/29/2024] Open
Abstract
Many biologists are interested in teaching computing skills or using computing in the classroom, despite not being formally trained in these skills themselves. Thus biologists may find themselves researching how to teach these skills, and therefore many individuals are individually attempting to discover resources and methods to do so. Recent years have seen an expansion of new technologies to assist in delivering course content interactively. Educational research provides insights into how learners absorb and process information during interactive learning. In this review, we discuss the value of teaching foundational computing skills to biologists, and strategies and tools to do so. Additionally, we review the literature on teaching practices to support the development of these skills. We pay special attention to meeting the needs of diverse learners, and consider how different ways of delivering course content can be leveraged to provide a more inclusive classroom experience. Our goal is to enable biologists to teach computational skills and use computing in the classroom successfully.
Collapse
Affiliation(s)
- April M. Wright
- Department of Biological Sciences, Southeastern Louisiana University, Hammond, LA, 70403, USA
| | - Rachel S. Schwartz
- Department of Biological Sciences, University of Rhode Island, Kingston, RI, 02881, USA
| | - Jamie R. Oaks
- Department of Biological Sciences, Auburn University, Auburn, AL, 36849, USA
| | | | - Sarah P. Flanagan
- School of Biological Sciences, University of Canterbury, Christchurch, 8042, New Zealand
| |
Collapse
|