Abstract: Systems and methods are provided herein for generating a classifier for phenotypic prediction. A computational causal network model representing a biological system includes a plurality of nodes and a plurality of edges connecting pairs of nodes. A first set of data corresponding to activities of a first subset of biological entities obtained under a first set of conditions is received, and a second set of data corresponding to activities of the first subset of biological entities obtained under a second set of conditions is received. A set of activity measures representing a difference between the first and second sets of data for a first subset of nodes is calculated. A set of activity values for a second subset of nodes, which are unmeasured, is generated. A classifier is generated for the phenotypes based on the set of activity measures, the set of activity values, or both.

Abstract: Systems and methods are described for quantifying the response of a biological system to one or more perturbations. First and second datasets corresponding to a response of a biological system to first and second treatments are received. A plurality of computational network models that represent the biological system are provided, each model including nodes representing a plurality of biological entities and edges representing relationships between the nodes in the model. A first set of scores is generated, representing the perturbation of the biological system based on the first dataset and the plurality of models, and a second set of scores representing the perturbation of the biological system based on the second dataset and the plurality of computational models. One or more biological impact factors are generated based on each of the first set and second set of scores that represent the biological impact of the perturbation on the biological system.

Abstract: Systems and methods are described for quantifying the response of a biological system to one or more perturbations. First and second datasets corresponding to a response of a biological system to first and second treatments are received. A plurality of computational network models that represent the biological system are provided, each model including nodes representing a plurality of biological entities and edges representing relationships between the nodes in the model. A first set of scores is generated, representing the perturbation of the biological system based on the first dataset and the plurality of models, and a second set of scores representing the perturbation of the biological system based on the second dataset and the plurality of computational models. One or more biological impact factors are generated based on each of the first set and second set of scores that represent the biological impact of the perturbation on the biological system.

Abstract: Systems and methods are described for quantifying the response of a biological system to one or more perturbations. First and second datasets corresponding to a response of a biological system to first and second treatments are received. A plurality of computational network models that represent the biological system are provided, each model including nodes representing a plurality of biological entities and edges representing relationships between the nodes in the model. A first set of scores is generated, representing the perturbation of the biological system based on the first dataset and the plurality of models, and a second set of scores representing the perturbation of the biological system based on the second dataset and the plurality of computational models. One or more biological impact factors are generated based on each of the first set and second set of scores that represent the biological impact of the perturbation on the biological system.

Abstract: Systems and methods are provided herein for generating a classifier for phenotypic prediction. A computational causal network model representing a biological system includes a plurality of nodes and a plurality of edges connecting pairs of nodes. A first set of data corresponding to activities of a first subset of biological entities obtained under a first set of conditions is received, and a second set of data corresponding to activities of the first subset of biological entities obtained under a second set of conditions is received. A set of activity measures representing a difference between the first and second sets of data for a first subset of nodes is calculated. A set of activity values for a second subset of nodes, which are unmeasured, is generated. A classifier is generated for the phenotypes based on the set of activity measures, the set of activity values, or both.

Abstract: Systems, computerized methods and products are disclosed herein for determining metrics for nodes in a network model of a biological system. Such systems and computerized methods can be used to quantify the response of a biological system to one or more perturbations based on measured activity data of a subset of entities in the biological system. Based on the activity data and a network model of the biological system, centrality values representative of the relative importance of a node in the network are derived. The centrality values are used for characterizing topological perturbations in the network, such as for performing sensitivity analysis, visualizing topological effects of a perturbation in the biological system, or deriving a score quantifying the response of the biological system to a perturbation such as exposure to a chemical agent.

Abstract: Systems and methods are directed to computerized methods and one or more computer processors for quantifying the perturbation of a biological system in response to an agent. A set of treatment data corresponding to a response of a biological system to an agent and a set of control data are received. A computational causal network model represents the biological system and includes nodes representing biological entities, edges representing relationships between the biological entities, and direction values representing the expected direction of change between the control data and the treatment data. Activity measures are calculated and represent a difference between the treatment data and the control data, and weight values are calculated for the nodes. A score for the computational model is generated representative of the perturbation of the biological system to the agent and is based on the direction values, the weight values and the activity measures.

Abstract: Systems and methods are described for quantifying the response of a biological system to one or more perturbations. First and second datasets corresponding to a response of a biological system to first and second treatments are received. A plurality of computational network models that represent the biological system are provided, each model including nodes representing a plurality of biological entities and edges representing relationships between the nodes in the model. A first set of scores is generated, representing the perturbation of the biological system based on the first dataset and the plurality of models, and a second set of scores representing the perturbation of the biological system based on the second dataset and the plurality of computational models. One or more biological impact factors are generated based on each of the first set and second set of scores that represent the biological impact of the perturbation on the biological system.