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Community-Driven Data Analysis Training for Biology.


ABSTRACT: 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.

SUBMITTER: Batut B 

PROVIDER: S-EPMC6296361 | biostudies-other | 2018 Jun

REPOSITORIES: biostudies-other

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Community-Driven Data Analysis Training for Biology.

Batut Bérénice B   Hiltemann Saskia S   Bagnacani Andrea A   Baker Dannon D   Bhardwaj Vivek V   Blank Clemens C   Bretaudeau Anthony A   Brillet-Guéguen Loraine L   Čech Martin M   Chilton John J   Clements Dave D   Doppelt-Azeroual Olivia O   Erxleben Anika A   Freeberg Mallory Ann MA   Gladman Simon S   Hoogstrate Youri Y   Hotz Hans-Rudolf HR   Houwaart Torsten T   Jagtap Pratik P   Larivière Delphine D   Le Corguillé Gildas G   Manke Thomas T   Mareuil Fabien F   Ramírez Fidel F   Ryan Devon D   Sigloch Florian Christoph FC   Soranzo Nicola N   Wolff Joachim J   Videm Pavankumar P   Wolfien Markus M   Wubuli Aisanjiang A   Yusuf Dilmurat D   Taylor James J   Backofen Rolf R   Nekrutenko Anton A   Grüning Björn B  

Cell systems 20180601 6


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.  ...[more]

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