Signaling pathway modeling for systematic study of diseases

Signaling pathways are a sequence of actions inside a cell, usually responsible for the transmission of a message from outside world to the nucleus. Finding disease-related signaling pathways is helpful in discovering the mechanism of the diseases, creating better drugs, and personalizing drugs for patients. Different Pathway analysis methods have been proposed to find and rank signaling pathways perturbed in a given phenotype. In this article, we review the approaches proposed by our research team to analyze the signaling pathways. These approaches are based on graphical models and formal methods for modeling signaling pathways. In the first method, a new pathway enrichment analysis method, BNrich, is introduced. This method has been applied on data related to systemic lupus erythematosus (SLE), to underscore key molecular characteristics of SLE pathogenesis, which may serve as effective targets for therapeutic intervention. After that, two formal methods are introduced, the first one models the signaling pathways using PRISM language and assign weights to genegene interactions, and the second uses Petri net for modeling, which have advantages over other formal methods, because of its graphical and hierarchical structure. Based on these proposed methods, two tools called FoPA and PAPet have been developed, in Python and R programming languages.

کلیدواژه ها:

signaling pathway ، graphical model ، formal method ، petri