title: SurvNet: a web server for identifying network-based biomarkers that most correlate with patient survival data.
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 biomarkers and display them through a user-friendly interface. SurvNet can be accessed at http://bioinformatics.mdanderson.org/main/SurvNet.
authors.affiliation: Chinese Academy of Sciences Key Laboratory of Computational Biology, Chinese Academy of Sciences and Max Planck Society (CAS-MPG) Partner Institute for Computational Biology, Shanghai Institutes for Biological Sciences, Chinese Academy of Sciences, Shanghai 200031, P.R. China.
authors.forename: Jun
authors.initials: J
authors.lastname: Li
authors.forename: Paul
authors.initials: P
authors.lastname: Roebuck
authors.forename: Stefan
authors.initials: S
authors.lastname: Grünewald
authors.forename: Han
authors.initials: H
authors.lastname: Liang
mesh_terms: D015415:Biomarkers / Q000032:analysis*; D053263:Gene Regulatory Networks; D006801:Humans; D020407:Internet; D025941:Protein Interaction Mapping; D012984:Software; D016019:Survival Analysis; D059467:Transcriptome
chemical_list: D015415:Biomarkers