Volume 41 Issue 6
Nov.  2020
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Hao Dai, Qi-Qi Jin, Lin Li, Luo-Nan Chen. Reconstructing gene regulatory networks in single-cell transcriptomic data analysis. Zoological Research, 2020, 41(6): 599-604. doi: 10.24272/j.issn.2095-8137.2020.215
Citation: Hao Dai, Qi-Qi Jin, Lin Li, Luo-Nan Chen. Reconstructing gene regulatory networks in single-cell transcriptomic data analysis. Zoological Research, 2020, 41(6): 599-604. doi: 10.24272/j.issn.2095-8137.2020.215

Reconstructing gene regulatory networks in single-cell transcriptomic data analysis

doi: 10.24272/j.issn.2095-8137.2020.215
Funds:  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)
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  • Corresponding author: E-mail: lnchen@sibs.ac.cn
  • Received Date: 2020-08-03
  • Accepted Date: 2020-10-20
  • Published Online: 2020-10-21
  • Publish Date: 2020-11-18
  • 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.
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