MPSO-CD: A Multi-objective Particle Swarm Optimization Community Detection Method for Identifying Disease Modules

The dysfunction of biological systems caused by disease-related genes is one of the inducements of complex diseases. To understand molecular mechanisms of complex diseases, the identification of disease-related gene modules in biological networks through community detection is emerging as a promising approach. However, most community detection methods are not suitable for biological networks because their topological structures are complex and the scale of biologically relevant modules are small. In this paper, a novel community detection method called MPSO-CD was proposed based on multi-objective particle swarm optimization, in which negative ratio association and ratio cut were employed as objective functions. Highlights of MPSO-CD are a mutation strategy based on clustering coefficient and the procedure of disease module screening referring to the internal connection density and functional similarity. Experimental results of social and synthetic complex networks indicate that MPSO-CD is comparable and often superior to four compared methods. Eventually, MPSO-CD is applied to the asthma gene co-expression network for identifying potential disease modules that provide the molecular mechanism information about asthma. Most of the captured modules have been proven to be associated with asthma through Gene Ontology and pathway enrichment analysis.