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US 2012/0258874 A1Published application
Interrogatory cell-based assays and uses thereof
AssigneeBerg Biosystems, LLC
InventorsNIVEN RAJIN NARAIN, RANGAPRASAD SARANGARAJAN, VIVEK K. VISHNUDAS
Life of this patent
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Abstract
Described herein is a discovery Platform Technology for analyzing a biological system or process (e.g., a disease condition, such as cancer) via model building.
Claims44
A method for identifying a modulator of a biological system, said method comprising:
- (1) establishing a model for the biological system, using cells associated with the biological system, to represents a characteristic aspect of the biological system;
- (2) obtaining a first data set from the model for the biological system, wherein the first data set represents expression levels of a plurality of genes in the cells associated with the biological system;
- (3) obtaining a second data set from the model for the biological system, wherein the second data set represents a functional activity or a cellular response of the cells associated with the biological system;
- (4) generating a consensus causal relationship network among the expression levels of the plurality of genes and the functional activity or cellular response based solely on the first data set and the second data set using a programmed computing device, wherein the generation of the consensus causal relationship network is not based on any known biological relationships other than the first data set and the second data set;
- (5) identifying, from the consensus causal relationship network, a causal relationship unique in the biological system, wherein a gene associated with the unique causal relationship is identified as a modulator of the biological system.
2 more elements
A method for identifying a modulator of a disease process, said method comprising:
- (1) establishing a disease model for the disease process, using disease related cells, to represents a characteristic aspect of the disease process;
- (2) obtaining a first data set from the disease model, wherein the first data set represents expression levels of a plurality of genes in the disease related cells;
- (3) obtaining a second data set from the disease model, wherein the second data set represents a functional activity or a cellular response of the disease related cells;
- (4) generating a consensus causal relationship network among the expression levels of the plurality of genes and the functional activity or cellular response based solely on the first data set and the second data set using a programmed computing device, wherein the generation of the consensus causal relationship network is not based on any known biological relationships other than the first data set and the second data set;
- (5) identifying, from the consensus causal relationship network, a causal relationship unique in the disease process, wherein a gene associated with the unique causal relationship is identified as a modulator of a disease process.
2 more elements
A method for providing a model for a biological system for use in a platform method, comprising:
- establishing a model for a biological system, using cells associated with the biological system, to represent a characteristic aspect of the biological system, wherein the model for the biological system is useful for generating data sets used in the platform method;
- thereby providing a model for a biological system for use in a platform method.
A method for obtaining a first data set and second data set from a model for a biological system for use in a platform method, comprising:
- (1) obtaining a first data set from the model for a biological system for use in a platform method, wherein the model for the biological system comprises cells associated with the biological system, and wherein the first data set represents expression levels of a plurality of genes in the cells associated with the biological system;
- (2) obtaining a second data set from the model for a biological system for use in the platform method, wherein the second data set represents a functional activity or a cellular response of the cells associated with the biological system;
- thereby obtaining a first data set and second data set from the model for the biological system for use in a platform method.
A method for identifying a modulator of a biological system, said method comprising:
- (1) generating a consensus causal relationship network among a first data set and second data set obtained from a model for the biological system, wherein the model comprises cells associated with the biological system, and wherein the first data set represents expression levels of a plurality of genes in the cells and the second data set represents a functional activity or a cellular response of the cells, using a programmed computing device, wherein the generation of the consensus causal relationship network is not based on any known biological relationships other than the first data set and the second data set;
- (2) identifying, from the consensus causal relationship network, a causal relationship unique in the biological system, wherein a gene associated with the unique causal relationship is identified as a modulator of the biological system;
- thereby identifying a modulator of a biological system.
A method for identifying a modulator of a biological system, said method comprising:
- 1) providing a consensus causal relationship network generated from a model for the biological system;
- 2) identifying, from the consensus causal relationship network, a causal relationship unique in the biological system, wherein a gene associated with the unique causal relationship is identified as a modulator of the biological system;
- thereby identifying a modulator of a biological system.
A method for providing a disease model for use in a platform method, comprising:
- establishing a disease model for a disease process, using disease related cells, to represent a characteristic aspect of the disease process,
- wherein the disease model is useful for generating disease model data sets used in the platform method;
- thereby providing a disease model for use in a platform method.
A method for obtaining a first data set and second data set from a disease model for use in a platform method, comprising:
- (1) obtaining a first data set from a disease model for use in a platform method, wherein the disease model comprises disease related cells, and wherein the first data set represents expression levels of a plurality of genes in the disease related cells;
- (2) obtaining a second data set from the disease model for use in a platform method, wherein the second data set represents a functional activity or a cellular response of the disease related cells;
- thereby obtaining a first data set and second data set from the disease model;
- thereby obtaining a first data set and second data set from a disease model for use in a platform method.
1 more element
A method for identifying a modulator of a disease process, said method comprising:
- (1) generating a consensus causal relationship network among a first data set and second data set obtained from a disease model, wherein the disease model comprises disease cells, and wherein the first data set represents expression levels of a plurality of genes in the disease related cells and the second data set represents a functional activity or a cellular response of the disease related cells, using a programmed computing device, wherein the generation of the consensus causal relationship network is not based on any known biological relationships other than the first data set and the second data set;
- (2) identifying, from the consensus causal relationship network, a causal relationship unique in the disease process, wherein a gene associated with the unique causal relationship is identified as a modulator of a disease process;
- thereby identifying a modulator of a disease process.
A method for identifying a modulator of a disease process, said method comprising:
- 1) providing a consensus causal relationship network generated from a disease model for the disease process;
- 2) identifying, from the consensus causal relationship network, a causal relationship unique in the disease process, wherein a gene associated with the unique causal relationship is identified as a modulator of a disease process;
- thereby identifying a modulator of a disease process.
Dependencies are inferred from the claim text.