A primer on deep learning in genomics
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Updated: Feb 2, 2026

Deep Learning-Based Segmentation of Cryo-Electron Tomograms
Published on: November 11, 2022
James Zou1,2,3, Mikael Huss4,5, Abubakar Abid6
1Department of Biomedical Data Science, Stanford University, Palo Alto, CA, USA. jamesz@stanford.edu.
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.
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