| 摘要 |
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. |
| 主权项 |
1. A computerized method for identifying biological entities that are representative of a phenotype of interest, comprising the steps of:
(a) providing, at a processing device, a computational causal network model that represents a biological system that contributes to the phenotype and includes: a plurality of nodes that represent biological entities in the biological system; and a plurality of edges connecting pairs of nodes among the plurality of nodes and representing relationships between the biological entities represented by the nodes; wherein one or more edges is associated with a direction value that represents a causal activation or causal suppression relationship between the biological entities represented by the nodes, and wherein each node is connected by an edge to at least one other node; (b) receiving, at the processing device, (i) a first set of data corresponding to activities of a first subset of biological entities obtained under a first set of conditions; and (ii) a second set of data corresponding to activities of the first subset of biological entities obtained under a second set of conditions different from the first set of conditions, wherein the first and second sets of conditions relate to the phenotype; (c) calculating, with the processing device, a set of activity measures for a first subset of nodes corresponding to the first subset of biological entities, the activity measure representing a difference between the first set of data and the second set of data; (d) generating, with the processing device, a set of activity values for a second subset of nodes representing candidates of biological entities that contribute to the phenotype but whose activities are not measured, based on the computational causal network model and the set of activity measures; (e) generating, with the processing device using a machine learning technique, a classifier for the phenotypes based on the set of activity measures, the set of activity values, or both. |
