IPromoter-Seqvec: identifying promoters using bidirectional long short-term memory and sequence-embedded features.

ABSTRACT:

Background

Promoters, non-coding DNA sequences located at upstream regions of the transcription start site of genes/gene clusters, are essential regulatory elements for the initiation and regulation of transcriptional processes. Furthermore, identifying promoters in DNA sequences and genomes significantly contributes to discovering entire structures of genes of interest. Therefore, exploration of promoter regions is one of the most imperative topics in molecular genetics and biology. Besides experimental techniques, computational methods have been developed to predict promoters. In this study, we propose iPromoter-Seqvec - an efficient computational model to predict TATA and non-TATA promoters in human and mouse genomes using bidirectional long short-term memory neural networks in

SUBMITTER: Nguyen-Vo TH 

PROVIDER: S-EPMC9531353 | biostudies-literature | 2022 Oct

REPOSITORIES: biostudies-literature