CYTOSCAPE: A MODELING PLATFORM FOR BIOMOLECULAR NETWORKS SUMMARY Cytoscape is an open source bioinformatics environment for biological network analysis, visualization and modeling. It has grown to become a standard resource in academia and industry, due mainly to its timeliness (it was one of the first tools for visualization of biological networks), open development model (it is still one of few such tools that is open-source) and public App interface (allowing anyone to add functionality to Cytoscape and attracting hundreds of third-party developers and industrial partners). Cytoscape usage continues to increase significantly, doubling over the past three years to ~208,000 downloads in 2016. The NIH has funded Cytoscape development since 2004 under the ?Continued Development and Maintenance of Software? group of programs (R01 GM070743). In this competitive renewal, we will improve, maintain, and support Cytoscape along four Specific Aims. First, we will substantially increase the resources available in Cytoscape for the study of human genetic variants in individual human genomes and across cohorts of individuals. We will ensure access to key molecular networks for humans and human disease, implement direct import of human sequence variants and add a network propagation engine for identifying genetic variants impacting the same network neighborhoods and pathways. Second, we will develop Cytoscape into a useful clinical recommendation system, where researchers, and ultimately clinicians, can score a patient as being part of a particular class (?e.g., case or control, disease subtype) based on the surrounding patient similarity network. This will be based on our recently developed netDx computational method that classifies patients into subtypes based on diverse clinical and genomic data. Third, we will develop a system of Cytoscape workflows based on Jupyter Notebooks and web services, allowing flexible automation, access to new data types, and more fluid interchange of network analyses. Fourth, we will maintain and disseminate Cytoscape using a modern software management process, and we will continue to work with scientific journals to integrate Cytoscape-based network and workflow viewers into scientific publications. Cytoscape is an important milepost on the road to developing large-scale ?circuit diagrams? of human biology and disease. Continued support of Cytoscape will allow other laboratories to avoid reinventing the same tools, time that can instead be devoted to more complex analyses or to basic research.
CYTOSCAPE: A MODELING PLATFORM FOR BIOMOLECULAR NETWORKS NARRATIVE Continued support of Cytoscape will allow NIH investigators to maintain and magnify their ongoing successful efforts to mine molecular networks for new pathways, biomarkers and individual variations underlying disease.
| Wang, Sheng; Ma, Jianzhu; Zhang, Wei et al. (2018) Typing tumors using pathways selected by somatic evolution. Nat Commun 9:4159 |
| Zhang, Wei; Bojorquez-Gomez, Ana; Velez, Daniel Ortiz et al. (2018) A global transcriptional network connecting noncoding mutations to changes in tumor gene expression. Nat Genet 50:613-620 |
| Pai, Shraddha; Bader, Gary D (2018) Patient Similarity Networks for Precision Medicine. J Mol Biol 430:2924-2938 |
| Huang, Justin K; Carlin, Daniel E; Yu, Michael Ku et al. (2018) Systematic Evaluation of Molecular Networks for Discovery of Disease Genes. Cell Syst 6:484-495.e5 |
| Ma, Jianzhu; Yu, Michael Ku; Fong, Samson et al. (2018) Using deep learning to model the hierarchical structure and function of a cell. Nat Methods 15:290-298 |
