天津师范大学学报（自然科学版）2024，Vol.44Issue(1)：1-12,12.DOI:10.19638/j.issn1671-1114.20240101
基于单细胞RNA测序数据的基因调控网络推断算法综述
Review of gene regulatory network inference algorithms based on single-cell RNA sequencing data
摘要
Abstract
Gene regulatory networks(GRN)can be inferred from the changes of gene expression.Single-cell RNA sequencing(scRNA-seq)technologies provide new possibilities for inferring GRNs of time-dependent biological processes such as cell cycle or differentiation,and GRN inference algorithm has become a relatively active research direction.Firstly,26 inference algorithms including three algorithms based on bulk RNA sequencing data and 23 algorithms based on scRNA-seq data(two algorithms based on Boolean network,three algorithms based on differential equations,five algorithms based on pseudo-time-series gene correlation integration strategy,four algorithms based on co-expression genes,three algorithms based on cell specif-ic,six algorithms based on deep learning)are reviewed.The method principles of the algorithms are described in detail as well as advantages and disadvantages of each algorithm,and the algorithms are compared comprehensively.And then the compara-tive studies on inference algorithms are analyzed,and the performance of 26 algorithms is simply evaluated using scRNA-seq data.Finally,the opportunities and challenges faced by current GRN inference algorithms are discussed.关键词
基因调控网络/单细胞RNA测序/网络推断算法/深度学习Key words
gene regulatory network/single-cell RNA sequencing/network inference algorithm/deep learning分类
信息技术与安全科学引用本文复制引用
张少强,潘镜伊..基于单细胞RNA测序数据的基因调控网络推断算法综述[J].天津师范大学学报（自然科学版）,2024,44(1):1-12,12.基金项目
国家自然科学基金资助项目(61572358) （61572358）
天津市自然科学基金重点资助项目(19JCZDJC35100). （19JCZDJC35100）
