Inferring cell cycle feedback regulation from gene expression data

Fulvia Ferrazzi, Felix B. Engel, Erxi Wu, Annie P. Moseman, Isaac S. Kohane, Riccardo Bellazzi, Marco F. Ramoni

Research output: Contribution to journalArticlepeer-review

Abstract

Feedback control is an important regulatory process in biological systems, which confers robustness against external and internal disturbances. Genes involved in feedback structures are therefore likely to have a major role in regulating cellular processes.Here we rely on a dynamic Bayesian network approach to identify feedback loops in cell cycle regulation. We analyzed the transcriptional profile of the cell cycle in HeLa cancer cells and identified a feedback loop structure composed of 10 genes. In silico analyses showed that these genes hold important roles in system's dynamics. The results of published experimental assays confirmed the central role of 8 of the identified feedback loop genes in cell cycle regulation.In conclusion, we provide a novel approach to identify critical genes for the dynamics of biological processes. This may lead to the identification of therapeutic targets in diseases that involve perturbations of these dynamics.

Original languageEnglish
Pages (from-to)565-575
Number of pages11
JournalJournal of Biomedical Informatics
Volume44
Issue number4
DOIs
Publication statusPublished - Aug 2011

Keywords

  • Cell cycle
  • Dynamic Bayesian network
  • Feedback
  • Gene expression

ASJC Scopus subject areas

  • Computer Science Applications
  • Health Informatics

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