DeepC: predicting 3D genome folding using megabase-scale transfer learning.
basic_science · Level V
Where this comes from
- Record sourced from PubMed, PMID 33046896.
- Also identified by DOI 10.1038/s41592-020-0960-3 and PMC identifier 7610627.
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Abstract
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.
Medical subject headings
- Genome, Human
- Genomics
- Models, Genetic
- Neural Networks, Computer