Literature DB >> 27603332

A vision for collaborative training infrastructure for bioinformatics.

Jason J Williams1, Tracy K Teal2.   

Abstract

In biology, a missing link connecting data generation and data-driven discovery is the training that prepares researchers to effectively manage and analyze data. National and international cyberinfrastructure along with evolving private sector resources place biologists and students within reach of the tools needed for data-intensive biology, but training is still required to make effective use of them. In this concept paper, we review a number of opportunities and challenges that can inform the creation of a national bioinformatics training infrastructure capable of servicing the large number of emerging and existing life scientists. While college curricula are slower to adapt, grassroots startup-spirited organizations, such as Software and Data Carpentry, have made impressive inroads in training on the best practices of software use, development, and data analysis. Given the transformative potential of biology and medicine as full-fledged data sciences, more support is needed to organize, amplify, and assess these efforts and their impacts.
© 2016 New York Academy of Sciences.

Keywords:  bioinformatics; cyberinfrastructure; education; open science; professional development; training

Mesh:

Year:  2016        PMID: 27603332     DOI: 10.1111/nyas.13207

Source DB:  PubMed          Journal:  Ann N Y Acad Sci        ISSN: 0077-8923            Impact factor:   5.691


  5 in total

1.  Community-Driven Data Analysis Training for Biology.

Authors:  Bérénice Batut; Saskia Hiltemann; Andrea Bagnacani; Dannon Baker; Vivek Bhardwaj; Clemens Blank; Anthony Bretaudeau; Loraine Brillet-Guéguen; Martin Čech; John Chilton; Dave Clements; Olivia Doppelt-Azeroual; Anika Erxleben; Mallory Ann Freeberg; Simon Gladman; Youri Hoogstrate; Hans-Rudolf Hotz; Torsten Houwaart; Pratik Jagtap; Delphine Larivière; Gildas Le Corguillé; Thomas Manke; Fabien Mareuil; Fidel Ramírez; Devon Ryan; Florian Christoph Sigloch; Nicola Soranzo; Joachim Wolff; Pavankumar Videm; Markus Wolfien; Aisanjiang Wubuli; Dilmurat Yusuf; James Taylor; Rolf Backofen; Anton Nekrutenko; Björn Grüning
Journal:  Cell Syst       Date:  2018-06-27       Impact factor: 10.304

2.  Unmet needs for analyzing biological big data: A survey of 704 NSF principal investigators.

Authors:  Lindsay Barone; Jason Williams; David Micklos
Journal:  PLoS Comput Biol       Date:  2017-10-19       Impact factor: 4.475

3.  'Students-as-partners' scheme enhances postgraduate students' employability skills while addressing gaps in bioinformatics education.

Authors:  Luciane V Mello; Luke Tregilgas; Gwen Cowley; Anshul Gupta; Fatima Makki; Anjeet Jhutty; Achchuthan Shanmugasundram
Journal:  High Educ Pedagog       Date:  2017-06-21

4.  Towards an Internet of Science.

Authors:  Jens Allmer
Journal:  J Integr Bioinform       Date:  2019-05-30

5.  An integrated, modular approach to data science education in microbiology.

Authors:  Kimberly A Dill-McFarland; Stephan G König; Florent Mazel; David C Oliver; Lisa M McEwen; Kris Y Hong; Steven J Hallam
Journal:  PLoS Comput Biol       Date:  2021-02-25       Impact factor: 4.475

  5 in total

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