DM-MOGA: a multi-objective optimization genetic algorithm for identifying disease modules of non-small cell lung cancer.

ABSTRACT:

Background

Constructing molecular interaction networks from microarray data and then identifying disease module biomarkers can provide insight into the underlying pathogenic mechanisms of non-small cell lung cancer. A promising approach for identifying disease modules in the network is community detection.

Results

In order to identify disease modules from gene co-expression networks, a community detection method is proposed based on multi-objective optimization genetic algorithm with decomposition. The method is named DM-MOGA and possesses two highlights. First, the boundary correction strategy is designed for the modules obtained in the process of local module detection and pre-simplification. Second, during the evolution, we introduce Davies-Bouldin index and clustering co

SUBMITTER: Shang J 

PROVIDER: S-EPMC9830734 | biostudies-literature | 2023 Jan

REPOSITORIES: biostudies-literature