Probabilistic boolean networks
AssigneesBoard of Regents, The University of Texas, The Texas A&M University System
InventorsIlya Shmulevich, Edward R. Dougherty, Wei Zhang
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Abstract
Embodiments of the invention encompass methods for modeling of complex systems, which include, but are not limited to gene regulatory networks, biological systems, and the like. Other embodiments of the invention include the development of computational tools for the identification and discovery of potential targets for therapeutic intervention in diseases such as cancer. The embodiments discussed utilize methods that model the potential effect of individual genes on the global dynamical network behavior, both from the view of random gene mutation as well as intervention in order to elicit desired network behavior.
Claims21
A method for constructing a model network comprising:
- (a) obtaining measurements of factors that influence a value of a node in a network;
- (b) determining a measure of association between a combination of network nodes associated with at least one other network node;
- (c) constructing a plurality of predictor functions for the at least one other network node given the combination of network nodes;
- (d) transforming the measure of association between the combination of network nodes and at least one other network node into a predictor function probability;
- and
- (e) constructing a network representative of a complex system utilizing the plurality of predictor functions and the predictor function probabilities.
A method for constructing a network representative of a biological system comprising:
- (a) obtaining measurement of factors in a biological system that influence a value of a node in a network;
- (b) selecting a combination of network nodes associated with a state of at least one other network node;
- (c) determining a measure of association between the combination of network nodes and at least one other network node;
- (d) constructing a plurality of predictor functions for a value of at least one other network node given the combination of network nodes;
- (e) transforming the measure of association between the combination of network nodes and the at least one other network node into a predictor function probability;
- and
- (f) constructing a network representative of a biological system utilizing the plurality of predictor functions and the predictor function probabilities.
An apparatus comprising a machine readable medium containing instructions which, when executed by a machine, cause the machine to perform operations comprising:
- (a) receiving values for a plurality of network nodes;
- (b) selecting a combination of network nodes associated with a state of at least one other network node;
- (c) determining a cumulative measure of association between the combination of network nodes and at least one other network node;
- (d) constructing a plurality of predictor functions for a value of at least one other network node given the combination of network nodes;
- (e) transforming the cumulative measure of association between the combination of network nodes and at least one other network node into a predictor function probability;
- and
- (f) constructing a network representative of a complex system utilizing the plurality predictor functions and the predictor function probabilities.
A method comprising:
- (a) identifying a plurality of network nodes related to a state of at least one other network node within a network, wherein each network node of the network includes a network node value which influences a gene expression state;
- (b) obtaining measurements of factors that influence a value of at least one network node;
- (c) constructing a plurality of predictor functions from a combination of network nodes utilizing at least one of the network node values for at least one target node;
- (d) determining a cumulative measure of association for combinations of network nodes;
- (e) transforming the cumulative measure of association into a probability that any one of a plurality of predictor functions is utilized to determine a state of at least one other node of a network;
- and
- (f) connecting a plurality of network node combinations to construct a probabilistic Boolean network.
Dependencies are inferred from the claim text.