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Controllability analysis of transcriptional regulatory networks for Saccharomyces cerevisiae

  • Suling Liu
  • , Pei Wang*
  • , Qiong Xu
  • , Aimin Chen
  • , Jinhu Lü
  • *Corresponding author for this work
  • Henan University

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Structural controllability of complex networks has been a research focus in recent years. However, few works considered the structural controllability of biological networks, especially for dynamic biological networks. In this paper, structural controllability of one static and five dynamic transcriptional regulatory networks (TRNs) for Saccharomyces cerevisiae (S. cerevisiae) have been investigated. The five dynamic networks included two endogenous and three exogenous ones. We clarified the controllability properties of these networks, as well as explored the differences among different types of networks. Our results revealed that the structural properties of different types of networks are significantly different. We found that the TRNs are rather difficult to be fully controlled. However, the dynamic TRNs were relatively easier to be controlled than the static one, and one needs relatively more external inputs to control the exogenous TRNs than the endogenous ones. Based on the structural controllability analysis of subnetworks with the same sizes, as well as randomly perturbed networks by preserving degree distributions, we further illustrated that the structural controllability of the six networks may be mainly dominated by their degree distributions. Our investigations clarify the control properties of TRNs in S. cerevisiae, it provides some insights on real-world control of biological networks.

Original languageEnglish
Title of host publicationProceedings
Subtitle of host publicationIECON 2018 - 44th Annual Conference of the IEEE Industrial Electronics Society
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages6172-6177
Number of pages6
ISBN (Electronic)9781509066841
DOIs
StatePublished - 26 Dec 2018
Event44th Annual Conference of the IEEE Industrial Electronics Society, IECON 2018 - Washington, United States
Duration: 20 Oct 201823 Oct 2018

Publication series

NameProceedings: IECON 2018 - 44th Annual Conference of the IEEE Industrial Electronics Society

Conference

Conference44th Annual Conference of the IEEE Industrial Electronics Society, IECON 2018
Country/TerritoryUnited States
CityWashington
Period20/10/1823/10/18

Keywords

  • Complex network
  • Degree distributions
  • Saccharomyces cerevisiae
  • Structural controllability
  • Transcriptional regulatory networks

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