| Literature DB >> 33583104 |
Alexander Ostrovsky1, Jennifer Hillman-Jackson2, Dave Bouvier2, Dave Clements1, Enis Afgan1, Daniel Blankenberg3, Michael C Schatz1, Anton Nekrutenko2, James Taylor1, The Galaxy Team1,2,3,4, Delphine Lariviere2.
Abstract
Modern biology continues to become increasingly computational. Datasets are becoming progressively larger, more complex, and more abundant. The computational savviness necessary to analyze these data creates an ongoing obstacle for experimental biologists. Galaxy (galaxyproject.org) provides access to computational biology tools in a web-based interface. It also provides access to major public biological data repositories, allowing private data to be combined with public datasets. Galaxy is hosted on high-capacity servers worldwide and is accessible for free, with an option to be installed locally. This article demonstrates how to employ Galaxy to perform biologically relevant analyses on publicly available datasets. These protocols use both standard and custom tools, serving as a tutorial and jumping-off point for more intensive and/or more specific analyses using Galaxy.Entities:
Keywords: Galaxy; computational biology; web application
Mesh:
Year: 2021 PMID: 33583104 DOI: 10.1002/cpz1.31
Source DB: PubMed Journal: Curr Protoc ISSN: 2691-1299