期刊
NATURE METHODS
卷 17, 期 11, 页码 1118-+出版社
NATURE PORTFOLIO
DOI: 10.1038/s41592-020-0960-3
关键词
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资金
- MRC [MC_UU_00016/14]
- Wellcome Trust [106130/Z/14/Z, 090532/Z/09/Z]
- Institutional Strategic Support Fund [105605/Z/14/Z]
- Wellcome Trust Genomic Medicine and Statistics PhD Program [203728/Z/16/Z, 203141/Z/16/Z]
- Stevenson Junior Research Fellowship at University College, Oxford
- European Research Council under the European Union [FP7/2007-2013, 617071]
- Common Fund of the Office of the Director of the National Institutes of Health
- NCI
- NHGRI
- NHLBI
- NIDA
- NIMH
- NINDS
- MRC [MC_UU_00016/14, MC_UU_12009/15, MR/N00969X/1] Funding Source: UKRI
- Wellcome Trust [203728/Z/16/Z] Funding Source: Wellcome Trust
DeepC uses transfer learning-based deep neural networks for predicting genome folding from megabase-scale DNA sequence. Predicting the impact of noncoding genetic variation requires interpreting it in the context of three-dimensional genome architecture. We have developed deepC, a transfer-learning-based deep neural network that accurately predicts genome folding from megabase-scale DNA sequence. DeepC predicts domain boundaries at high resolution, learns the sequence determinants of genome folding and predicts the impact of both large-scale structural and single base-pair variations.
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