Abstract: Systems and methods for modeling the interactions of the several genes, proteins and other components of a cell, employing mathematical techniques to represent the interrelationships between the cell components and the manipulation of the dynamics of the cell to determine which components of a cell may be targets for interaction with therapeutic agents. A first such method is based on a cell simulation approach in which a cellular biochemical network intrinsic to a phenotype of the cell is simulated by specifying its components and their interrelationships. The various interrelationships are represented with one or more mathematical equations which are solved to simulate a first state of the cell. The simulated network is then perturbed by deleting one or more components, changing the concentration of one or more components, or modifying one or more mathematical equations representing the interrelationships between one or more of the components.

Abstract: Systems and methods are presented for cell simulation and cell state prediction. For example, a cellular biochemical network intrinsic to a phenotype of a cell can be simulated by specifying its components and their interrelationships. The various interrelationships can be represented with one or more mathematical equations which can be solved to simulate a first state of the cell. The simulated network can then be perturbed, and the equations representing the perturbed network can be solved to simulate a second state of the cell which can then be compared to the first state, identifying the effect of such perturbation on the network, and thereby identifying one or more components as targets. Alternatively, components of a cell can be identified as targets for interaction with therapeutic agents based upon an analytical approach, in which a stable phenotype of a cell is specified and correlated to the state of the cell and the role of that cellular state to its operation.

Abstract: Systems and methods for modeling the interactions of the several genes, proteins and other components of a cell, employing mathematical techniques to represent the interrelationships between the cell components and the manipulation of the dynamics of the cell to determine which components of a cell may be targets for interaction with therapeutic agents. A first such method is based on a cell simulation approach in which a cellular biochemical network intrinsic to a phenotype of the cell is simulated by specifying its components and their interrelationships. The various interrelationships are represented with one or more mathematical equations which are solved to simulate a first state of the cell. The simulated network is then perturbed by deleting one or more components, changing the concentration of one or more components, or modifying one or more mathematical equations representing the interrelationships between one or more of the components.

Abstract: Presented herein are techniques and methodologies for creating large-scale data-driven models of biological systems and exemplary applications thereof including drug discovery and industrial applications. Exemplary embodiments include creating a core skeletal simulation (scaleable to any size) from known biological information, collecting quantitative and qualitative experimental data to constrain the simulation, creating a probable reactions database, integrating the core skeletal simulation, the database of probable reactions, and static and dynamical time course measurements to generate an ensemble of biological network structures and their corresponding molecular concentration profiles and phenotypic outcomes that approximate output of the original biological network used for prediction, and finally experimentally validating and iteratively refining the model.

Abstract: Systems and methods for modeling the interactions of the several genes, proteins and other components of a cell, employing mathematical techniques to represent the interrelationships between the cell components and the manipulation of the dynamics of the cell to determine which components of a cell may be targets for interaction with therapeutic agents. A first such method is based on a cell simulation approach in which a cellular biochemical network intrinsic to a phenotype of the cell is simulated by specifying its components and their interrelationships. The various interrelationships are represented with one or more mathematical equations which are solved to simulate a first state of the cell. The simulated network is then perturbed by deleting one or more components, changing the concentration of one or more components, or modifying one or more mathematical equations representing the interrelationships between one or more of the components.