Adaptive intervention in probabilistic boolean networks
نویسندگان
چکیده
منابع مشابه
Intervention in context-sensitive probabilistic Boolean networks
MOTIVATION Intervention in a gene regulatory network is used to help it avoid undesirable states, such as those associated with a disease. Several types of intervention have been studied in the framework of a probabilistic Boolean network (PBN), which is essentially a finite collection of Boolean networks in which at any discrete time point the gene state vector transitions according to the rul...
متن کاملIntervention in Context-Sensitive Probabilistic Boolean Networks Revisited
An approximate representation for the state space of a context-sensitive probabilistic Boolean network has previously been proposed and utilized to devise therapeutic intervention strategies. Whereas the full state of a context-sensitive probabilistic Boolean network is specified by an ordered pair composed of a network context and a gene-activity profile, this approximate representation collap...
متن کاملState reduction for network intervention in probabilistic Boolean networks
MOTIVATION A key goal of studying biological systems is to design therapeutic intervention strategies. Probabilistic Boolean networks (PBNs) constitute a mathematical model which enables modeling, predicting and intervening in their long-run behavior using Markov chain theory. The long-run dynamics of a PBN, as represented by its steady-state distribution (SSD), can guide the design of effectiv...
متن کاملGene perturbation and intervention in probabilistic Boolean networks.
MOTIVATION A major objective of gene regulatory network modeling, in addition to gaining a deeper understanding of genetic regulation and control, is the development of computational tools for the identification and discovery of potential targets for therapeutic intervention in diseases such as cancer. We consider the general question of the potential effect of individual genes on the global dy...
متن کاملMappings between probabilistic Boolean networks
Probabilistic Boolean Networks (PBNs) comprise a graphical model based on uncertain rule-based dependencies between nodes and have been proposed as a model for genetic regulatory networks. As with any algebraic structure, the characterization of important mappings between PBNs is critical for both theory and application. This paper treats the construction of mappings to alter PBN structure whil...
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ژورنال
عنوان ژورنال: Bioinformatics
سال: 2009
ISSN: 1367-4803,1460-2059
DOI: 10.1093/bioinformatics/btp349