Modeling transcriptional regulation of model species with deep learning.

TitleModeling transcriptional regulation of model species with deep learning.
Publication TypeJournal Article
Year of Publication2021
AuthorsCofer, EM, Raimundo, J, Tadych, A, Yamazaki, Y, Wong, AK, Theesfeld, CL, Levine, MS, Troyanskaya, OG
JournalGenome Res
Date Published2021 Jun
KeywordsAnimals, Caenorhabditis elegans, Deep Learning, Drosophila melanogaster, Gene Expression Regulation, Mice, Zebrafish

<p>To enable large-scale analyses of transcription regulation in model species, we developed DeepArk, a set of deep learning models of the -regulatory activities for four widely studied species: , , , and DeepArk accurately predicts the presence of thousands of different context-specific regulatory features, including chromatin states, histone marks, and transcription factors. In vivo studies show that DeepArk can predict the regulatory impact of any genomic variant (including rare or not previously observed) and enables the regulatory annotation of understudied model species.</p>

Alternate JournalGenome Res
PubMed ID33888512
PubMed Central IDPMC8168591
Grant ListR01 GM071966 / GM / NIGMS NIH HHS / United States
R35 GM118147 / GM / NIGMS NIH HHS / United States
T32 HG003284 / HG / NHGRI NIH HHS / United States