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Source code:

Online implementation:

developed by Polina Belokopytova, Miroslav Nuriddinov, Evgeniy Mozheiko, Daniil Fishman and Veniamin Fishman


3DPredictor is machine-learning based method, which allows obtaining high-quality predictions of chromatin interactions in mammalian cells using information on gene expression and CTCF-binding. One can use 3DPredictor to predict ectopic interactions which appear after chromosomal rearrangements or to predict cell-type specific promoter-enhancer contacts in normal genome. Both model training code and trained models are available at github. Web-implementation is also provided ( and requires no bioinformatic skills to predict contacts for a region of interest.

How to cite

P.S. Belokopytova, M.A. Nuriddinov, E.A. Mozheiko, D. Fishman and V. Fishman Quantitative prediction of enhancer-promoter interactions. Genome Res. 2020 Jan; 30(1): 72–84. doi: 10.1101/gr.249367.119