PROTEOMICSBioinformaticsPeer-reviewed journal article
ProNetView-ccRCC: A web-based portal to interactively explore clear cell renal cell carcinoma proteogenomics networks
Selim KalaycıiD, Francesca PetraliaiD, Pei WangiD, Zeynep Hulya GumusiD
Abstract
To better understand the molecular basis of cancer, the NCIs Clinical Proteomics Tumor Analysis Consortium (CPTAC) has been performing comprehensive large-scale proteogenomic characterizations of multiple cancer types. Gene/protein regulatory networks has subsequently been derived based on these proteogenomic profiles, which serve as useful tools to gain system-level understanding of the molecular regulatory factories underlying the diseases. On the other hand, it remains a challenge to effectively visualize and navigate the resulting network models, which capture higher order structures in the proteogenomic profiles. There is a pressing need to have a new open community resource tool for intuitive visual exploration, interpretation and communication of these gene/protein regulatory networks by the cancer research community. In this work, we introduce ProNetView-ccRCC (http://ccrcc.cptac-network-view.org/), an interactive web-based network exploration portal for investigating phosphopeptide co-expression network inferred based on the CPTAC clear cell renal cell carcinoma (ccRCC) phosphoproteomics data. ProNetView-ccRCC enables quick, user-intuitive visual interactions with the ccRCC tumor phosphoprotein co-expression network comprised of 3,614 genes, as well as 30 functional pathway-enriched network modules. Users can interact with the network portal and can conveniently query for association between abundance of each phosphopeptide in the network and clinical variables such as tumor grade.
- organism: human
- assay: proteomics
- research focus: gene regulatory network inference
- research focus: database / resource
- research focus: benchmarking
- approach: statistical model
- approach: experimental assay
- Citations
- 7
- FWCI
- 0.41
- Field percentile
- top 48%
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