Existing methods to visualize data on biological networks quickly become inadequate as network size and data complexity increase. To address this challenge, Bing Zhang, Ph.D., assistant professor of Biomedical Informatics, and colleagues developed NetGestalt, a web application for integrating “omics” data – such as genomics, proteomics and metabolomics – over biological networks.
The investigators describe NetGestalt and demonstrate its features and potential in the July issue of Nature Methods. They used NetGestalt to evaluate gene expression in the advancement of colorectal cancer. The analysis revealed previously undiscovered dynamic gene expression patterns that suggest new directions for anti-inflammatory therapeutic interventions. They also evaluated genetic variation data from The Cancer Genome Atlas glioblastoma multiforme (GBM) study. This analysis identified known networks involved in GBM and pointed to a novel network that may provide new insights into both tumor progression and clinical management of GBM.
NetGestalt will allow investigators to simultaneously visualize different types of data within the same biological network, facilitating data integration and discovery.
This research was supported by grants from the National Institutes of Health (GM088822, CA159988, MH096972) and was conducted in part using the resources of the Advanced Computing Center for Research and Education at Vanderbilt University.
