X-Module: A novel fusion measure to associate co-expressed gene modules from condition-specific expression profiles

A gene co-expression network (CEN) is of biological interest, since co-expressed genes share commonfunctions and biological processes or pathways. Finding relationships among modules can reveal inter-modularpreservation, and similarity in transcriptome, functional, and biological behaviors among modules of the sameor two different datasets. There is no method which explores the one-to-one relationships and one-to-manyrelationships among modules extracted from control and disease samples based on both topological andsemantic similarity using both microarray and RNA seq data. In this work, we propose a novel fusion measureto detect mapping between modules from two sets of co-expressed modules extracted from control and diseasestages of Alzheimer’s disease (AD) and Parkinson’s disease (PD) datasets. Our measure considers bothtopological and biological information of a module and is an estimation of four parameters, namely, semanticsimilarity, eigengene correlation, degree difference, and the number of common genes. We analyze the consensus modules shared between both control and disease stages in terms of their association with diseases. Wealso validate the close associations between human and chimpanzee modules and compare with the state-ofthe-art method. Additionally, we propose two novel observations on the relationships between modules forfurther analysis.

MIPCE: An MI-based protein complex extraction technique.

Protein–protein interaction (PPI) networks are believed to be important sources of information related to biological processes and complex metabolic functions of the cell. Identifying protein complexes is of great importance for understanding cellular organization and functions of organisms. In this work, a method is proposed, referred to as MIPCE, to find protein complexes in a PPI network based on mutual information.MIPCE has been biologically validated by GO-based score and satisfactory results have been obtained. We have also compared our method with some wellknown methods and obtained better results in terms of various parameters such as precession, recall and F-measure.