Discovering gene sets underlying the expression of a given phenotype is of great
importance, as many phenotypes are the result of complex gene-gene interactions. Gene …

Relevant gene selection is crucial for analyzing cancer gene expression datasets including
two types of tumors in cancer classification. Intrinsic interactions among selected genes …

This paper deals with the problems of cancer classification and grouped gene selection. The
weighted gene co-expression network on cancer microarray data is employed to identify …

Gene co-expression network analysis is an effective method for predicting gene functions
and disease biomarkers. However, few studies have systematically identified co-expressed …

Gene coexpression networks are a useful tool for summarizing transcriptomic data and
providing insight into patterns of gene regulation in a variety of species. Though there has …

Abstract Background Human Immunodeficiency Virus-1 (HIV) infection frequently results in
neurocognitive impairment. While the cause remains unclear, recent gene expression …

The study of gene relationships and their effect on biological function and phenotype is a
focal point in systems biology. Gene co-expression networks built using microarray …

Ataxia oculomotor apraxia type 2 (AOA2) is a rare autosomal recessive cerebellar ataxia.
Recent evidence suggests that the protein defective in this syndrome, senataxin (SETX) …

In this paper, we present a new approach for mining weighted networks to identify densely
connected modules such as quasi-cliques. Quasi-cliques are densely connected …

Purpose Prostate cancer is one of the leading causes of cancer death for male. In the
present study, we applied an integrated bioinformatics approach to provide a novel …