4.7 Article

Community-Driven Data Analysis Training for Biology

期刊

CELL SYSTEMS
卷 6, 期 6, 页码 752-+

出版社

CELL PRESS
DOI: 10.1016/j.cels.2018.05.012

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资金

  1. Collaborative Research Centre 992 Medical Epigenetics (DFG) [SFB 992/1 2012]
  2. German Federal Ministry of Education and Research (BMBF) [031 A538A RBC]
  3. NIH [U41 HG006620, R01 AI134384-01]
  4. NSF [1661497]
  5. Div Of Biological Infrastructure
  6. Direct For Biological Sciences [1661497] Funding Source: National Science Foundation

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The primary problem with the explosion of biomedical datasets is not the data, not computational resources, and not the required storage space, but the general lack of trained and skilled researchers to manipulate and analyze these data. Eliminating this problem requires development of comprehensive educational resources. Here we present a community-driven framework that enables modern, interactive teaching of data analytics in life sciences and facilitates the development of training materials. The key feature of our system is that it is not a static but a continuously improved collection of tutorials. By coupling tutorials with a web-based analysis framework, biomedical researchers can learn by performing computation themselves through a web browser without the need to install software or search for example datasets. Our ultimate goal is to expand the breadth of training materials to include fundamental statistical and data science topics and to precipitate a complete re-engineering of undergraduate and graduate curricula in life sciences. This project is accessible at https://training.galaxyproject.org.

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