Inferring context-sensitive probablistic boolean networks from gene expression data under multi-biological conditions

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Abstract

In recent years biological microarrays have emerged as a high-throughput data acquisition technology in bioinformatics. In conjunction with this, there is an increasing need to develop frameworks for the formal analysis of biological pathways. A modeling approach defined as Probabilistic Boolean Networks (PBNs) was proposed for inferring genetic regulatory networks [1]. This technology,
an extension of Boolean Networks [2], is able to capture the time-varying dependencies with deterministic probabilities for a series of sets of predictor functions.
Original languageEnglish
Pages (from-to)63
Number of pages2
JournalBMC Systems Biology
Volume1
Issue numberSuppl 1
DOIs
Publication statusPublished - 2007
EventBioSysBio 2007: Systems Biology, Bioinformatics and Synthetic Biology - Manchester, United Kingdom
Duration: 11 Jan 200713 Jan 2007

Keywords

  • gene expression profiles has
  • biomedicine
  • context sensitive
  • boolean networks

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