Learning the histone codes with large genomic windows and three-dimensional chromatin interactions using transformer

Abstract

Existing deep learning-based approaches for the prediction of gene expression by histone modifications (HMs) can only focus on narrow and linear genomic regions around promoters. Here, the authors address these problems by developing a transformer-based deep learning architecture named Chromoformer.