INFERENCE OF TRANSITION PROBABILITIES BETWEEN THE ATTRACTORS IN BOOLEAN NETWORKS WITH PERTURBATION

Le Yu, Steven Watterson, Stephen Marshall, Peter Ghazal

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This paper investigates the inference of Boolean networks with perturbation (BNp) from simulated data and observed data. We interpret the discretised gene expression levels as attractor states of the underlying network and use the sequence of attractor states to determine the model. We consider the case where a complete sequence of attractors is known and the case where the known attractor states are arrived at by sampling from an underlying sequence of attractors. We apply the resulting algorithm to the interferon regulatory network using gene expression data taken from murine bone-derived macrophage cells infected with cytomegalovirus.

Original languageEnglish
Title of host publication2009 IEEE INTERNATIONAL WORKSHOP ON GENOMIC SIGNAL PROCESSING AND STATISTICS (GENSIPS 2009)
Place of PublicationNEW YORK
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Pages100-103
Number of pages4
ISBN (Print)978-1-4244-4531-8
Publication statusPublished - 2009
Event7th IEEE International Workshop on Genomic Signal Processing and Statistics (GENSIPS 2009) - Minneapolis
Duration: 17 May 200919 May 2009

Conference

Conference7th IEEE International Workshop on Genomic Signal Processing and Statistics (GENSIPS 2009)
CityMinneapolis
Period17/05/0919/05/09

Keywords

  • GENE REGULATORY NETWORKS
  • MODEL

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