High-throughput data production technologies, particularly ‘next-generation’ DNA sequencing, have ushered in widespread and disruptive changes to biomedical research. Making sense of the large datasets produced by these technologies requires sophisticated statistical and computational methods, as well as substantial computational power. This has led to an acute crisis in life sciences, as researchers without informatics training attempt to perform computation-dependent analyses. Since 2005, the Galaxy project has worked to address this problem by providing a framework that makes advanced computational tools usable by non experts. Galaxy seeks to make data-intensive research more accessible, transparent and reproducible by providing a Web-based environment in which users can perform computational analyses and have all of the details automatically tracked for later inspection, publication, or reuse. In this report we highlight recently added features enabling biomedical analyses on a large scale.
The Galaxy platform for accessible, reproducible and collaborative biomedical analyses: 2016 update
E. Afgan,D. Baker,Marius van den Beek,Daniel J. Blankenberg,Dave Bouvier,Martin Čech,J. Chilton,D. Clements,Nate Coraor,Carl Eberhard,B. Grüning,Aysam Guerler,Jennifer Hillman-Jackson,G. V. Kuster,Eric Rasche,N. Soranzo,Nitesh Turaga,James Taylor,A. Nekrutenko,Jeremy Goecks
Published 2016 in Nucleic Acids Res.
ABSTRACT
PUBLICATION RECORD
- Publication year
2016
- Venue
Nucleic Acids Res.
- Publication date
2016-05-02
- Fields of study
Biology, Medicine, Computer Science
- Identifiers
- External record
- Source metadata
Semantic Scholar, PubMed
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REFERENCES
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