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

Yu, Le and Marshall, Stephen (2007) Inferring context-sensitive probablistic boolean networks from gene expression data under multi-biological conditions. BMC Systems Biology, 1 (Suppl ). p. 63. ISSN 1752-0509

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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.

    Creators(s): Yu, Le and Marshall, Stephen ORCID logoORCID: https://orcid.org/0000-0001-7079-5628;
    Item type:Article
    ID code:30373
    Keywords:gene expression profiles has, biomedicine, context sensitive, boolean networks, Biology, Structural Biology, Modelling and Simulation, Molecular Biology, Applied Mathematics
    Subjects:Science > Natural history > Biology
    Department:Faculty of Engineering > Electronic and Electrical Engineering
    Depositing user: Pure Administrator
    Date deposited:08 Apr 2011 08:42
    Last modified:20 Jan 2021 19:15
    URI:https://strathprints.strath.ac.uk/id/eprint/30373
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