Reconstructing gene regulatory networks in single-cell transcriptomic data analysis

Zool Res. 2020 Nov 18;41(6):599-604. doi: 10.24272/j.issn.2095-8137.2020.215.

Abstract

Gene regulatory networks play pivotal roles in our understanding of biological processes/mechanisms at the molecular level. Many studies have developed sample-specific or cell-type-specific gene regulatory networks from single-cell transcriptomic data based on a large amount of cell samples. Here, we review the state-of-the-art computational algorithms and describe various applications of gene regulatory networks in biological studies.

基因调控网络对在分子水平上理解生物过程和机制起着至关重要的作用。很多研究基于单细胞转录组数据中的大量细胞样本,开发了一系列算法构建样本特异或细胞类型特异的基因调控网络。该文系统回顾了目前最新的基于单细胞转录组数据构建基因调控网络的算法,特别是一个细胞数据构建一个网络的理论和方法(CSN: cell-specific network),与现有的单个细胞型(cell type)的基因调控网络不同,CSN是一个细胞构建一个基因调控网络的方法,该文进一步描述了其在生物学研究中的各种应用。.

Keywords: Cell-specific network; Cell-type-specific network; Computational algorithm; Gene regulatory network; Sample-specific network; Single-cell RNA sequencing.

Publication types

  • Review

MeSH terms

  • Animals
  • Computer Simulation*
  • Gene Regulatory Networks / physiology*
  • Models, Genetic*
  • Sequence Analysis, RNA / methods*
  • Single-Cell Analysis
  • Transcriptome

Grants and funding

This study was supported by the National Key Research and Development Program of China (2017YFA0505500), Strategic Priority Research Program of the Chinese Academy of Sciences (XDB38040400), National Science Foundation of China (31771476 and 31930022), and Shanghai Municipal Science and Technology Major Project (2017SHZDZX01)