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Bianchi L, Liò P. Opportunities for community awareness platforms in personal genomics and bioinformatics education. Brief Bioinform 2018; 18:1082-1090. [PMID: 27580620 DOI: 10.1093/bib/bbw078] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2016] [Indexed: 01/16/2023] Open
Abstract
Precision and personalized medicine will be increasingly based on the integration of various type of information, particularly electronic health records and genome sequences. The availability of cheap genome sequencing services and the information interoperability will increase the role of online bioinformatics analysis. Being on the Internet poses constant threats to security and privacy. While we are connected and we share information, websites and internet services collect various types of personal data with or without the user consent. It is likely that genomics will merge with the internet culture of connectivity. This process will increase incidental findings, exposure and vulnerability. Here we discuss the social vulnerability owing to the genome and Internet combined security and privacy weaknesses. This urges more efforts in education and social awareness on how biomedical data are analysed and transferred through the internet and how inferential methods could integrate information from different sources. We propose that digital social platforms, used for raising collective awareness in different fields, could be developed for collaborative and bottom-up efforts in education. In this context, bioinformaticians could play a meaningful role in mitigating the future risk of digital-genomic divide.
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Chakraborty C, George Priya Doss C, Zhu H, Agoramoorthy G. Rising Strengths Hong Kong SAR in Bioinformatics. Interdiscip Sci 2016; 9:224-236. [PMID: 26961385 PMCID: PMC7091071 DOI: 10.1007/s12539-016-0147-x] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2015] [Revised: 12/07/2015] [Accepted: 01/08/2016] [Indexed: 12/18/2022]
Abstract
Hong Kong's bioinformatics sector is attaining new heights in combination with its economic boom and the predominance of the working-age group in its population. Factors such as a knowledge-based and free-market economy have contributed towards a prominent position on the world map of bioinformatics. In this review, we have considered the educational measures, landmark research activities and the achievements of bioinformatics companies and the role of the Hong Kong government in the establishment of bioinformatics as strength. However, several hurdles remain. New government policies will assist computational biologists to overcome these hurdles and further raise the profile of the field. There is a high expectation that bioinformatics in Hong Kong will be a promising area for the next generation.
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Affiliation(s)
- Chiranjib Chakraborty
- Department of Bio-informatics, School of Computer and Information Sciences, Galgotias University, Greater Noida, UP, 201306, India
- Department of Computer Sciences, Hong Kong Baptist University, Kowloon Tong, Hong Kong
| | - C George Priya Doss
- Medical Biotechnology Division, School of BioSciences and Technology, VIT University, Vellore, TN, 632014, India
| | - Hailong Zhu
- Department of Computer Sciences, Hong Kong Baptist University, Kowloon Tong, Hong Kong.
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Sims D, Ponting CP, Heger A. CGAT: a model for immersive personalized training in computational genomics. Brief Funct Genomics 2015; 15:32-7. [PMID: 25981124 PMCID: PMC4812590 DOI: 10.1093/bfgp/elv021] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/15/2023] Open
Abstract
How should the next generation of genomics scientists be trained while simultaneously pursuing high quality and diverse research? CGAT, the Computational Genomics Analysis and Training programme, was set up in 2010 by the UK Medical Research Council to complement its investment in next-generation sequencing capacity. CGAT was conceived around the twin goals of training future leaders in genome biology and medicine, and providing much needed capacity to UK science for analysing genome scale data sets. Here we outline the training programme employed by CGAT and describe how it dovetails with collaborative research projects to launch scientists on the road towards independent research careers in genomics.
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Bolger AM, Lohse M, Usadel B. Trimmomatic: a flexible trimmer for Illumina sequence data. BIOINFORMATICS (OXFORD, ENGLAND) 2014; 151:3-12. [PMID: 24695404 DOI: 10.1111/ppl.12098] [Citation(s) in RCA: 49] [Impact Index Per Article: 4.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/30/2013] [Revised: 07/30/2013] [Accepted: 08/15/2013] [Indexed: 05/09/2023]
Abstract
MOTIVATION Although many next-generation sequencing (NGS) read preprocessing tools already existed, we could not find any tool or combination of tools that met our requirements in terms of flexibility, correct handling of paired-end data and high performance. We have developed Trimmomatic as a more flexible and efficient preprocessing tool, which could correctly handle paired-end data. RESULTS The value of NGS read preprocessing is demonstrated for both reference-based and reference-free tasks. Trimmomatic is shown to produce output that is at least competitive with, and in many cases superior to, that produced by other tools, in all scenarios tested. AVAILABILITY AND IMPLEMENTATION Trimmomatic is licensed under GPL V3. It is cross-platform (Java 1.5+ required) and available at http://www.usadellab.org/cms/index.php?page=trimmomatic CONTACT usadel@bio1.rwth-aachen.de SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
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Affiliation(s)
- Anthony M Bolger
- Department Metabolic Networks, Max Planck Institute of Molecular Plant Physiology, Am Mühlenberg 1, 14476 Golm,Institut für Biologie I, RWTH Aachen, Worringer Weg 3, 52074 Aachen and Institute of Bio- and Geosciences: Plant Sciences, Forschungszentrum Jülich, Leo-Brandt-Straße, 52425 Jülich, GermanyDepartment Metabolic Networks, Max Planck Institute of Molecular Plant Physiology, Am Mühlenberg 1, 14476 Golm,Institut für Biologie I, RWTH Aachen, Worringer Weg 3, 52074 Aachen and Institute of Bio- and Geosciences: Plant Sciences, Forschungszentrum Jülich, Leo-Brandt-Straße, 52425 Jülich, Germany
| | - Marc Lohse
- Department Metabolic Networks, Max Planck Institute of Molecular Plant Physiology, Am Mühlenberg 1, 14476 Golm,Institut für Biologie I, RWTH Aachen, Worringer Weg 3, 52074 Aachen and Institute of Bio- and Geosciences: Plant Sciences, Forschungszentrum Jülich, Leo-Brandt-Straße, 52425 Jülich, Germany
| | - Bjoern Usadel
- Department Metabolic Networks, Max Planck Institute of Molecular Plant Physiology, Am Mühlenberg 1, 14476 Golm,Institut für Biologie I, RWTH Aachen, Worringer Weg 3, 52074 Aachen and Institute of Bio- and Geosciences: Plant Sciences, Forschungszentrum Jülich, Leo-Brandt-Straße, 52425 Jülich, GermanyDepartment Metabolic Networks, Max Planck Institute of Molecular Plant Physiology, Am Mühlenberg 1, 14476 Golm,Institut für Biologie I, RWTH Aachen, Worringer Weg 3, 52074 Aachen and Institute of Bio- and Geosciences: Plant Sciences, Forschungszentrum Jülich, Leo-Brandt-Straße, 52425 Jülich, Germany
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Henry VJ, Bandrowski AE, Pepin AS, Gonzalez BJ, Desfeux A. OMICtools: an informative directory for multi-omic data analysis. DATABASE-THE JOURNAL OF BIOLOGICAL DATABASES AND CURATION 2014; 2014:bau069. [PMID: 25024350 PMCID: PMC4095679 DOI: 10.1093/database/bau069] [Citation(s) in RCA: 135] [Impact Index Per Article: 13.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 01/19/2023]
Abstract
Recent advances in ‘omic’ technologies have created unprecedented opportunities for biological research, but current software and database resources are extremely fragmented. OMICtools is a manually curated metadatabase that provides an overview of more than 4400 web-accessible tools related to genomics, transcriptomics, proteomics and metabolomics. All tools have been classified by omic technologies (next-generation sequencing, microarray, mass spectrometry and nuclear magnetic resonance) associated with published evaluations of tool performance. Information about each tool is derived either from a diverse set of developers, the scientific literature or from spontaneous submissions. OMICtools is expected to serve as a useful didactic resource not only for bioinformaticians but also for experimental researchers and clinicians. Database URL:http://omictools.com/
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Affiliation(s)
- Vincent J Henry
- Haute-Normandie-INSERM ERI-28, Institute for Research and Innovation in Biomedicine of Rouen University, 76183 Rouen, France, Center for Research in Biological Systems, University of California, San Diego, 9500 Gilman Dr. La Jolla, CA 92093, USA and STATSARRAY, 76300 Sotteville-lès-Rouen, France
| | - Anita E Bandrowski
- Haute-Normandie-INSERM ERI-28, Institute for Research and Innovation in Biomedicine of Rouen University, 76183 Rouen, France, Center for Research in Biological Systems, University of California, San Diego, 9500 Gilman Dr. La Jolla, CA 92093, USA and STATSARRAY, 76300 Sotteville-lès-Rouen, France
| | - Anne-Sophie Pepin
- Haute-Normandie-INSERM ERI-28, Institute for Research and Innovation in Biomedicine of Rouen University, 76183 Rouen, France, Center for Research in Biological Systems, University of California, San Diego, 9500 Gilman Dr. La Jolla, CA 92093, USA and STATSARRAY, 76300 Sotteville-lès-Rouen, France
| | - Bruno J Gonzalez
- Haute-Normandie-INSERM ERI-28, Institute for Research and Innovation in Biomedicine of Rouen University, 76183 Rouen, France, Center for Research in Biological Systems, University of California, San Diego, 9500 Gilman Dr. La Jolla, CA 92093, USA and STATSARRAY, 76300 Sotteville-lès-Rouen, France
| | - Arnaud Desfeux
- Haute-Normandie-INSERM ERI-28, Institute for Research and Innovation in Biomedicine of Rouen University, 76183 Rouen, France, Center for Research in Biological Systems, University of California, San Diego, 9500 Gilman Dr. La Jolla, CA 92093, USA and STATSARRAY, 76300 Sotteville-lès-Rouen, France
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Abstract
Motivation: Although many next-generation sequencing (NGS) read preprocessing tools already existed, we could not find any tool or combination of tools that met our requirements in terms of flexibility, correct handling of paired-end data and high performance. We have developed Trimmomatic as a more flexible and efficient preprocessing tool, which could correctly handle paired-end data. Results: The value of NGS read preprocessing is demonstrated for both reference-based and reference-free tasks. Trimmomatic is shown to produce output that is at least competitive with, and in many cases superior to, that produced by other tools, in all scenarios tested. Availability and implementation: Trimmomatic is licensed under GPL V3. It is cross-platform (Java 1.5+ required) and available at http://www.usadellab.org/cms/index.php?page=trimmomatic Contact:usadel@bio1.rwth-aachen.de Supplementary information:Supplementary data are available at Bioinformatics online.
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Affiliation(s)
- Anthony M Bolger
- Department Metabolic Networks, Max Planck Institute of Molecular Plant Physiology, Am Mühlenberg 1, 14476 Golm,Institut für Biologie I, RWTH Aachen, Worringer Weg 3, 52074 Aachen and Institute of Bio- and Geosciences: Plant Sciences, Forschungszentrum Jülich, Leo-Brandt-Straße, 52425 Jülich, GermanyDepartment Metabolic Networks, Max Planck Institute of Molecular Plant Physiology, Am Mühlenberg 1, 14476 Golm,Institut für Biologie I, RWTH Aachen, Worringer Weg 3, 52074 Aachen and Institute of Bio- and Geosciences: Plant Sciences, Forschungszentrum Jülich, Leo-Brandt-Straße, 52425 Jülich, Germany
| | - Marc Lohse
- Department Metabolic Networks, Max Planck Institute of Molecular Plant Physiology, Am Mühlenberg 1, 14476 Golm,Institut für Biologie I, RWTH Aachen, Worringer Weg 3, 52074 Aachen and Institute of Bio- and Geosciences: Plant Sciences, Forschungszentrum Jülich, Leo-Brandt-Straße, 52425 Jülich, Germany
| | - Bjoern Usadel
- Department Metabolic Networks, Max Planck Institute of Molecular Plant Physiology, Am Mühlenberg 1, 14476 Golm,Institut für Biologie I, RWTH Aachen, Worringer Weg 3, 52074 Aachen and Institute of Bio- and Geosciences: Plant Sciences, Forschungszentrum Jülich, Leo-Brandt-Straße, 52425 Jülich, GermanyDepartment Metabolic Networks, Max Planck Institute of Molecular Plant Physiology, Am Mühlenberg 1, 14476 Golm,Institut für Biologie I, RWTH Aachen, Worringer Weg 3, 52074 Aachen and Institute of Bio- and Geosciences: Plant Sciences, Forschungszentrum Jülich, Leo-Brandt-Straße, 52425 Jülich, Germany
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