Predictive Modeling of Gene Expression and Localization of DNA Binding Site Using Deep Convolutional Neural Networks.

ABSTRACT: Despite the sequencing revolution, large swaths of the genomes sequenced to date lack any information about the arrangement of transcription factor binding sites on regulatory DNA. Massively Parallel Reporter Assays (MPRAs) have the potential to dramatically accelerate our genomic annotations by making it possible to measure the gene expression levels driven by thousands of mutational variants of a regulatory region. However, the interpretation of such data often assumes that each base pair in a regulatory sequence contributes independently to gene expression. To enable the analysis of this data in a manner that accounts for possible correlations between distant bases along a regulatory sequence, we developed the Deep learning Adaptable Regulatory Sequence Identifier (DARSI). This convolut

SUBMITTER: Karshenas A 

PROVIDER: S-EPMC11702772 | biostudies-literature | 2024 Dec

REPOSITORIES: biostudies-literature