SNPeBoT: a tool for predicting transcription factor allele specific binding.

ABSTRACT:

Background

Mutations in non-coding regulatory regions of DNA may lead to disease through the disruption of transcription factor binding. However, our understanding of binding patterns of transcription factors and the effects that changes to their binding sites have on their action remains limited. To address this issue we trained a Deep learning model to predict the effects of Single Nucleotide Polymorphisms (SNP) on transcription factor binding. Allele specific binding (ASB) data from Chromatin Immunoprecipitation sequencing (ChIP-seq) experiments were paired with high sequence-identity DNA binding Domains assessed in Protein Binding Microarray (PBM) experiments. For each transcription factor a paired DNA binding Domain was selected from which we derived E-score profiles for refer

SUBMITTER: Gohl P 

PROVIDER: S-EPMC11895208 | biostudies-literature | 2025 Mar

REPOSITORIES: biostudies-literature