Pre-disease Detection Using Dynamical Network Biomarkers in Gene Regulatory Networks with Cell-to-cell Interaction

Y. Saito*, H. Sasahara*, X. Shen*, J. Peña Ramirez*, J. Imura*, M. Oku, K. Aihara

*Corresponding author for this work

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

1 Scopus citations

Abstract

Dynamical Network Biomarkers (DNB) theory has been proposed as a method for detecting diseases at a very early stage. The progression of a disease can be regarded as a bifurcation phenomenon of the underlying dynamical system associated with the corresponding gene network. By identifying large fluctuations of the gene expression level occurring just before the bifurcation, we can detect the pre-disease stage without identifying the mathematical model of the dynamical system. However, the existing DNB theory mainly focuses on a single gene network representing averaged dynamics of multiple cells not explicitly handling a group of cells with cell-to-cell interaction. In this study, we extend the DNB theory to the case where cell-to-cell interaction is also taken into account. Ultimately, our analysis reveals that the pre-disease stage can be detected from the observation of the average gene expression when the bifurcation is induced by the intrinsic dynamics of the cells, whereas it remains undetectable when the bifurcation is produced by the interaction.

Original languageEnglish
Title of host publicationIFAC-PapersOnLine
EditorsHideaki Ishii, Yoshio Ebihara, Jun-ichi Imura, Masaki Yamakita
PublisherElsevier B.V.
Pages6459-6464
Number of pages6
Edition2
ISBN (Electronic)9781713872344
DOIs
StatePublished - 2023/07/01
Event22nd IFAC World Congress - Yokohama, Japan
Duration: 2023/07/092023/07/14

Publication series

NameIFAC-PapersOnLine
Number2
Volume56
ISSN (Electronic)2405-8963

Conference

Conference22nd IFAC World Congress
Country/TerritoryJapan
CityYokohama
Period2023/07/092023/07/14

Keywords

  • Cell-to-cell interaction
  • dynamical network biomarker
  • gene regulatory networks

ASJC Scopus subject areas

  • Control and Systems Engineering

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