PhyloPGM: boosting regulatory function prediction accuracy using evolutionary information.

ABSTRACT:

Motivation

The computational prediction of regulatory function associated with a genomic sequence is of utter importance in -omics study, which facilitates our understanding of the underlying mechanisms underpinning the vast gene regulatory network. Prominent examples in this area include the binding prediction of transcription factors in DNA regulatory regions, and predicting RNA-protein interaction in the context of post-transcriptional gene expression. However, existing computational methods have suffered from high false-positive rates and have seldom used any evolutionary information, despite the vast amount of available orthologous data across multitudes of extant and ancestral genomes, which readily present an opportunity to improve the accuracy of existing computational meth

SUBMITTER: Ahsan F 

PROVIDER: S-EPMC9235490 | biostudies-literature | 2022 Jun

REPOSITORIES: biostudies-literature