3Dpredictor aimed to infer 3-dimensional interactions of chromatin, and particularly promoter enhancer interactions, in normal and rearranged genomes, using available epigenetic data. They benchmarked existing statistical approach and found that its predictive power is overestimated due to peculiar properties of biological data. Thus, we have taken a challenge to develop a new machine learning algorithm for quantitative prediction of genome architecture based on broadly available epigenetic datasets.

Belokopytova, P. S., Nuriddinov, M. A., Mozheiko, E. A., Fishman, D., & Fishman, V. (2020). Quantitative prediction of enhancer–promoter interactions. Genome research, 30(1), 72-84.

3D Predictor test case:

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