Abstract
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.
| Original language | English (US) |
|---|---|
| Pages (from-to) | W3-W10 |
| Journal | Nucleic acids research |
| Volume | 44 |
| Issue number | W1 |
| DOIs | |
| State | Published - Jul 8 2016 |
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All Science Journal Classification (ASJC) codes
- Genetics
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}
The Galaxy platform for accessible, reproducible and collaborative biomedical analyses : 2016 update. / Afgan, Enis; Baker, Dannon; van den Beek, Marius; Blankenberg, Daniel; Bouvier, Dave; Čech, Martin; Chilton, John; Clements, Dave; Coraor, Nate; Eberhard, Carl; Grüning, Björn; Guerler, Aysam; Hillman-Jackson, Jennifer; Von Kuster, Greg; Rasche, Eric; Soranzo, Nicola; Turaga, Nitesh; Taylor, James; Nekrutenko, Anton; Goecks, Jeremy.
In: Nucleic acids research, Vol. 44, No. W1, 08.07.2016, p. W3-W10.Research output: Contribution to journal › Article
TY - JOUR
T1 - The Galaxy platform for accessible, reproducible and collaborative biomedical analyses
T2 - 2016 update
AU - Afgan, Enis
AU - Baker, Dannon
AU - van den Beek, Marius
AU - Blankenberg, Daniel
AU - Bouvier, Dave
AU - Čech, Martin
AU - Chilton, John
AU - Clements, Dave
AU - Coraor, Nate
AU - Eberhard, Carl
AU - Grüning, Björn
AU - Guerler, Aysam
AU - Hillman-Jackson, Jennifer
AU - Von Kuster, Greg
AU - Rasche, Eric
AU - Soranzo, Nicola
AU - Turaga, Nitesh
AU - Taylor, James
AU - Nekrutenko, Anton
AU - Goecks, Jeremy
PY - 2016/7/8
Y1 - 2016/7/8
N2 - 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.
AB - 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.
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UR - http://www.scopus.com/inward/citedby.url?scp=84973094812&partnerID=8YFLogxK
U2 - 10.1093/nar/gkw343
DO - 10.1093/nar/gkw343
M3 - Article
C2 - 27137889
AN - SCOPUS:84973094812
VL - 44
SP - W3-W10
JO - Nucleic Acids Research
JF - Nucleic Acids Research
SN - 0305-1048
IS - W1
ER -