NOGEA: Network-Oriented Gene Entropy Approach for Dissecting Disease Comorbidity and Drug Repositioning

BioRxiv : the Preprint Server for Biology
Z. GuoYonghua Wang


Rapid development of high-throughput technologies has permitted the identification of an increasing number of disease-associated genes (DAGs), which are important for understanding disease initiation and developing precision therapeutics. However, DAGs often contain large amounts of redundant or false positive information, leading to difficulties in quantifying and prioritizing potential relationships between these DAGs and human diseases. In this study, a network-oriented gene entropy approach (NOGEA) is proposed for accurately inferring master genes that contribute to specific diseases by quantitatively calculating their perturbation abilities on directed disease-specific gene networks. In addition, we confirmed that the master genes identified by NOGEA have a high reliability for predicting disease-specific initiation events and progression risk. Master genes may also be used to extract the underlying information of different diseases, thus revealing mechanisms of disease comorbidity. More importantly, approved therapeutic targets are topologically localized in a small neighborhood of master genes on the interactome network, which provides a new way for predicting new drug-disease associations. Through this method, 11 old dr...Continue Reading

Related Concepts

Somatic Mutation
Genetic Analysis
Carcinoma, Transitional Cell
Nucleic Acid Sequencing
Cancer Gene Mutation
Urothelial Carcinoma

Related Feeds

BioRxiv & MedRxiv Preprints

BioRxiv and MedRxiv are the preprint servers for biology and health sciences respectively, operated by Cold Spring Harbor Laboratory. Here are the latest preprint articles (which are not peer-reviewed) from BioRxiv and MedRxiv.

Cancer Genomics (Preprints)

Cancer genomics employ high-throughput technologies to identify the complete catalog of somatic alterations that characterize the genome, transcriptome and epigenome of cohorts of tumor samples. Discover the latest preprints here.

Related Papers

Journal of Epidemiology
Etsuji SuzukiEiji Yamamoto
Proceedings of the National Academy of Sciences of the United States of America
David Fisman, Ashleigh Tuite
Journal of Neural Transmission. Supplementum
J M Rabey
Etsuji SuzukiToshihide Tsuda
© 2020 Meta ULC. All rights reserved