@article{4109,
  keywords = {Animals, Mice, Caenorhabditis elegans, Gene Expression Regulation, Drosophila melanogaster, Zebrafish, Deep Learning},
  author = {Evan Cofer and Jo{\~a}o Raimundo and Alicja Tadych and Yuji Yamazaki and Aaron Wong and Chandra Theesfeld and Michael Levine and Olga Troyanskaya},
  title = {Modeling transcriptional regulation of model species with deep learning.},
  abstract = { <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> },
  year = {2021},
  journal = {Genome Res},
  volume = {31},
  pages = {1097-1105},
  month = {2021 Jun},
  issn = {1549-5469},
  doi = {10.1101/gr.266171.120},
  language = {eng},
}