iEnhancer-DCLA: using the original sequence to identify enhancers and their strength based on a deep learning framework

• Published in: BMC bioinformatics Vol. 23; no. 1; pp. 1 - 16
• Main Authors: Liao, Meng, Zhao, Jian-ping, Tian, Jing, Zheng, Chun-Hou
• Format: Journal Article
• Language: English
• Published: London BioMed Central Ltd 14.11.2022; BioMed Central; BMC
• Subjects: Algorithms; Artificial neural networks; Attention mechanism; Bidirectional long short-term memory network; Binding sites; Chromatin; Convolutional neural network; Datasets; Deep learning; DNA sequencing; Enhancer; Enhancers; Entanglement; Experiments; Feature extraction; Gene expression; Genetic research; Genetic transcription; Genomes; Identification and classification; k-mers; Long short-term memory; Machine learning; Mathematical analysis; Methods; Neural networks; Nucleotide sequencing; Nucleotides; Transcription factors; Word embedding; China

Enhancers are small regions of DNA that bind to proteins, which enhance the transcription of genes. The enhancer may be located upstream or downstream of the gene. It is not necessarily close to the gene to be acted on, because the entanglement structure of chromatin allows the positions far apart i...