Affiliation:
1. School of Computer and Communication Engineering Beijing Advanced Innovation Center for Materials Genome Engineering University of Science and Technology Beijing Beijing 100083 China
2. Shunde Innovation School University of Science and Technology Beijing Foshan 528399 China
3. State Key Laboratory of Medical Molecular Biology Department of Biochemistry and Molecular Biology Institute of Basic Medical Sciences School of Basic Medicine Chinese Academy of Medical Sciences Peking Union Medical College Beijing 100005 China
Abstract
BackgroundAs parts of the cis‐regulatory mechanism of the human genome, interactions between distal enhancers and proximal promoters play a crucial role. Enhancers, promoters, and enhancer‐promoter interactions (EPIs) can be detected using many sequencing technologies and computation models. However, a systematic review that summarizes these EPI identification methods and that can help researchers apply and optimize them is still needed.ResultsIn this review, we first emphasize the role of EPIs in regulating gene expression and describe a generic framework for predicting enhancer‐promoter interaction. Next, we review prediction methods for enhancers, promoters, loops, and enhancer‐promoter interactions using different data features that have emerged since 2010, and we summarize the websites available for obtaining enhancers, promoters, and enhancer‐promoter interaction datasets. Finally, we review the application of the methods for identifying EPIs in diseases such as cancer.ConclusionsThe advance of computer technology has allowed traditional machine learning, and deep learning methods to be used to predict enhancer, promoter, and EPIs from genetic, genomic, and epigenomic features. In the past decade, models based on deep learning, especially transfer learning, have been proposed for directly predicting enhancer‐promoter interactions from DNA sequences, and these models can reduce the parameter training time required of bioinformatics researchers. We believe this review can provide detailed research frameworks for researchers who are beginning to study enhancers, promoters, and their interactions.
Funder
National Key Research and Development Program of China
National Natural Science Foundation of China
Subject
Applied Mathematics,Computer Science Applications,Biochemistry, Genetics and Molecular Biology (miscellaneous),Modeling and Simulation