Probabilistic Boolean networks: a rule-based uncertainty model for gene regulatory networks
نویسندگان
چکیده
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Probabilistic Boolean networks: a rule-based uncertainty model for gene regulatory networks
MOTIVATION Our goal is to construct a model for genetic regulatory networks such that the model class: (i) incorporates rule-based dependencies between genes; (ii) allows the systematic study of global network dynamics; (iii) is able to cope with uncertainty, both in the data and the model selection; and (iv) permits the quantification of the relative influence and sensitivity of genes in their...
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A significant amount of attention has recently been focused on modeling of gene regulatory networks. Two frequently used large-scale modeling frameworks are Bayesian networks (BNs) and Boolean networks, the latter one being a special case of its recent stochastic extension, probabilistic Boolean networks (PBNs). PBN is a promising model class that generalizes the standard rule-based interaction...
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High-throughput genomic technologies such as microarrays are now allowing scientists to acquire extensive information on gene activities of thousands of genes in cells at any physiological state. It has long been known that genes and their products in cells are not independent in the sense that the activation of genes with subsequent production of proteins is typically jointly dependent on the ...
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probabilistic boolean networks the modeling and control of probabilistic boolean networks the modeling and control of probabilistic boolean networks: the modeling and control probabilistic boolean networks society for industrial probabilistic boolean networks the modeling and control of probabilistic control of boolean networks with multiple from boolean to probabilistic boolean networks as mod...
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ژورنال
عنوان ژورنال: Bioinformatics
سال: 2002
ISSN: 1367-4803,1460-2059
DOI: 10.1093/bioinformatics/18.2.261