Article

Explainable models using transcription factor binding and epigenome patterns at promoters reveal disease-associated genes and their regulators in the context of cell-types

2024-05-08

Abstract excerpt

Understanding genome-wide epigenetic regulation of diseases is important in establishing pathogenic factors and could aid in disease diagnosis, prognosis, and therapeutics. In this study, we have utilized transcription factors (TFs) and co-factor profiles (n=823) as features in machine learning models to link them to various diseases. Further, along with TFs and co-factor profiles, histone modifications ChIP-seq (...

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Literature Corpus work: 007592d7-d725-5bbd-a0e4-36594a3c563a
DOI: 10.1101/2024.05.06.592622

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