Adapting Community Detection Algorithms for Disease Module Identification in Heterogeneous Biological Networks.

ABSTRACT: Biological networks catalog the complex web of interactions happening between different molecules, typically proteins, within a cell. These networks are known to be highly modular, with groups of proteins associated with specific biological functions. Human diseases often arise from the dysfunction of one or more such proteins of the biological functional group. The ability, to identify and automatically extract these modules has implications for understanding the etiology of different diseases as well as the functional roles of different protein modules in disease. The recent DREAM challenge posed the problem of identifying disease modules from six heterogeneous networks of proteins/genes. There exist many community detection algorithms, but all of them are not adaptable to the biological

SUBMITTER: Tripathi B 

PROVIDER: S-EPMC6424898 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature