| Literature DB >> 30478442 |
James Zou1,2,3, Mikael Huss4,5, Abubakar Abid6, Pejman Mohammadi7,8, Ali Torkamani7,8, Amalio Telenti9,10.
Abstract
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.Entities:
Mesh:
Year: 2018 PMID: 30478442 DOI: 10.1038/s41588-018-0295-5
Source DB: PubMed Journal: Nat Genet ISSN: 1061-4036 Impact factor: 38.330