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 ![]() | Item type: | Article |
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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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