SurvNet: a web server for identifying network-based biomarkers that most correlate with patient survival data.

Nucleic Acids Research
Jun LiHan Liang

Abstract

An important task in biomedical research is identifying biomarkers that correlate with patient clinical data, and these biomarkers then provide a critical foundation for the diagnosis and treatment of disease. Conventionally, such an analysis is based on individual genes, but the results are often noisy and difficult to interpret. Using a biological network as the searching platform, network-based biomarkers are expected to be more robust and provide deep insights into the molecular mechanisms of disease. We have developed a novel bioinformatics web server for identifying network-based biomarkers that most correlate with patient survival data, SurvNet. The web server takes three input files: one biological network file, representing a gene regulatory or protein interaction network; one molecular profiling file, containing any type of gene- or protein-centred high-throughput biological data (e.g. microarray expression data or DNA methylation data); and one patient survival data file (e.g. patients' progression-free survival data). Given user-defined parameters, SurvNet will automatically search for subnetworks that most correlate with the observed patient survival data. As the output, SurvNet will generate a list of network biom...Continue Reading

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Citations

Sep 28, 2013·Modern Pathology : an Official Journal of the United States and Canadian Academy of Pathology, Inc·Carlos E Parra-HerranBradley J Quade
May 9, 2014·Bioinformatics·Rotem Ben-HamoSol Efroni
Jan 7, 2015·Journal of Cellular and Molecular Medicine·Hao ChenYunfeng Cheng
Aug 17, 2016·Cancer Informatics·Seyedsasan HashemikhabirSarath Chandra Janga
Oct 3, 2017·Briefings in Bioinformatics·Duanchen SunLing-Yun Wu

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Methods Mentioned

BETA
protein array

Software Mentioned

GeneCard
GraphViz
SurvNet

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