A primer on deep learning in genomics
Author(s) -
James Zou,
Mikael Huss,
Abubakar Abid,
Pejman Mohammadi,
Ali Torkamani,
Amalio Telenti
Publication year - 2018
Publication title -
nature genetics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 18.861
H-Index - 573
eISSN - 1546-1718
pISSN - 1061-4036
DOI - 10.1038/s41588-018-0295-5
Subject(s) - deep learning , genomics , primer (cosmetics) , biology , perspective (graphical) , artificial intelligence , computational biology , genome , computer science , class (philosophy) , data science , genetics , gene , chemistry , organic chemistry
Deep learning methods are a class of machine learning techniques capable of identifying highly complex patterns in large datasets. Here, we provide a perspective and primer on deep learning applications for genome analysis. We discuss successful applications in the fields of regulatory genomics, variant calling and pathogenicity scores. We include general guidance for how to effectively use deep learning methods as well as a practical guide to tools and resources. This primer is accompanied by an interactive online tutorial.
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