Inference of transition probabilities between the attractors in Boolean networks with perturbation

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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 publicationUnknown Host Publication
PublisherIEEE
Number of pages4
DOIs
Publication statusPublished (in print/issue) - 2009
EventGenomic Signal Processing and Statistics, 2009. GENSIPS 2009. IEEE International Workshop -
Duration: 1 Jan 2009 → …

Conference

ConferenceGenomic Signal Processing and Statistics, 2009. GENSIPS 2009. IEEE International Workshop
Period1/01/09 → …

Keywords

  • logic
  • boolean network with perturbation
  • bnp

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