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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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Enis Afgan
Johns Hopkins University
Dannon Baker
Johns Hopkins University
Marius van den Beek
Centre National de la Recherche Scientifique
Nucleic Acids Research
Johns Hopkins University
Pennsylvania State University
Sorbonne Université
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Afgan et al. (Mon,) studied this question.
synapsesocial.com/papers/69db1c4800ab073a278396f8 — DOI: https://doi.org/10.1093/nar/gkw343
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