Probabilistic Boolean networks: a rule-based uncertainty model for gene regulatory networks
TLDR
Probabilistic Boolean Networks (PBN) are introduced that share the appealing rule-based properties of Boolean networks, but are robust in the face of uncertainty.Abstract:
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 interactions with other genes. Results: We introduce Probabilistic Boolean Networks (PBN) that share the appealing rule-based properties of Boolean networks, but are robust in the face of uncertainty. We show how the dynamics of these networks can be studied in the probabilistic context of Markov chains, with standard Boolean networks being special cases. Then, we discuss the relationship between PBNs and Bayesian networks—a family of graphical models that explicitly represent probabilistic relationships between variables. We show how probabilistic dependencies between a gene and its parent genes, constituting the basic building blocks of Bayesian networks, can be obtained from PBNs. Finally, we present methods for quantifying the influence of genes on other genes, within the context of PBNs. Examples illustrating the above concepts are presented throughout the paper.read more
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References
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TL;DR: The recent concept of the loop-characteristic state, defined as the logical state located at the level of the thresholds involved in the loop, together with its application, are presented and their applications are discussed.
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Mathematical Modeling of Gene Networks
TL;DR: This work was supported by National Institutes of Health grants T32 NS07373, R01 RR11626, and P01 NS38310.
Journal ArticleDOI
Gene expression profiling, genetic networks, and cellular states: an integrating concept for tumorigenesis and drug discovery
TL;DR: A global (genome-wide) view of "gene function" in the regulation of the dynamic relationship between proliferation, differentiation, and apoptosis can provide new insights into cellular homeostasis and the origins of neoplasia.