Boosting tissue-specific prediction of active cis-regulatory regions through deep learning and Bayesian optimization techniques.

ABSTRACT:

Background

Cis-regulatory regions (CRRs) are non-coding regions of the DNA that fine control the spatio-temporal pattern of transcription; they are involved in a wide range of pivotal processes such as the development of specific cell-lines/tissues and the dynamic cell response to physiological stimuli. Recent studies showed that genetic variants occurring in CRRs are strongly correlated with pathogenicity or deleteriousness. Considering the central role of CRRs in the regulation of physiological and pathological conditions, the correct identification of CRRs and of their tissue-specific activity status through Machine Learning methods plays a major role in dissecting the impact of genetic variants on human diseases. Unfortunately, the problem is still open, though some promising r

SUBMITTER: Cappelletti L 

PROVIDER: S-EPMC9743524 | biostudies-literature | 2022 Dec

REPOSITORIES: biostudies-literature