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DEEP SEA IMPLEMENTATION IN PYTORCH [IN PROGRESS]

DeepSEA is a deep learning-based algorithmic framework for predicting the chromatin effects of sequence alterations with single nucleotide sensitivity. DeepSEA can accurately predict the epigenetic state of a sequence, including transcription factors binding, DNase I sensitivities and histone marks in multiple cell types, and further utilize this capability to predict the chromatin effects of sequence variants and prioritize regulatory variants.

Jian Zhou, Olga G. Troyanskaya. Predicting the Effects of Noncoding Variants with Deep learning-based Sequence Model. Nature Methods (2015).

REFERENCES

Predicting effects of noncoding variants with deep learning-based sequence model | Github https://github.com/PuYuQian/PyDeepSEA/blob/master/DeepSEA_train.py https://github.com/jiawei6636/Bioinfor_DeepSEA

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