The Collaboration and Service component of the National Resource for Network Biology (NRNB) aims to identify collaborations that leverage our technology projects in developing new network methods, and to broaden the application of existing network analysis tools to a wide range of biomedical research domains. Our collaborations range from the use of Cytoscape as a research tool for network analysis and visualization to the development of Cytoscape apps for custom data types and analyses, new Internet-based Cytoscape Cyberinfrastructure components, application of other network and pathways tools and resources for network biology, and to users of NRNB's high performance computing cluster. Using these tools, we have fostered numerous discoveries in a variety of disease areas, such as hereditary spastic paraplegia, frontal temporal dementia, Alzheimer's disease, diabetes, anorexia nervosa, glaucoma, heart disease, leukemia, autism, malaria, and many types of cancer. Our tools and methods are also being applied in collaborative studies of the mechanisms underlying inflammation, stem cell differentiation, B-cell differentiation, ciliogenesis, cell-cell communication, transcriptional regulation, oxidative stress responses, DNA repair, cancer stem cells, viral infection, and wound healing, as well as general interactome, proteomics, and metabolomics research. Beyond our network analysis collaborations, we also engage in collaborations to develop new network biology methods and tools, often to produce free, open source Cytoscape apps, which can then be used by the entire network biology community. The diversity of NRNB collaboration projects can also be characterized as spanning every stage of a 4-stage technology development model: (1) Identifying a problem, biological question and target community, (2) Developing a new method or approach as a solution, and establishing a proof of concept, (3) Implementing a solution as a software tool or technology, and (4) Enabling and achieving broad adoption of the method via your tool or technology. The NRNB maintains staff at each member site to identify, screen and manage collaboration and service projects. In the past 4 years, we have maintained 60-80 active projects at any given time and have established a total of ~150 collaborations. With our broad outreach efforts, NRNB collaborations span 11 US states and 17 countries. As of July 2014, we report 47 publications resulting from NRNB collaboration and service projects. These publications have already been cited over 5,300 times. Notably, 20 of these publications are in Nature, Science and Cell family journals. .
| Buckley, Alexandra R; Ideker, Trey; Carter, Hannah et al. (2018) Exome-wide analysis of bi-allelic alterations identifies a Lynch phenotype in The Cancer Genome Atlas. Genome Med 10:69 |
| Wang, Sheng; Ma, Jianzhu; Zhang, Wei et al. (2018) Typing tumors using pathways selected by somatic evolution. Nat Commun 9:4159 |
| Zhang, Wei; Ma, Jianzhu; Ideker, Trey (2018) Classifying tumors by supervised network propagation. Bioinformatics 34:i484-i493 |
| Nikolayeva, Iryna; Guitart Pla, Oriol; Schwikowski, Benno (2018) Network module identification-A widespread theoretical bias and best practices. Methods 132:19-25 |
| 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 |
| Reznik, Ed; Luna, Augustin; Aksoy, Bülent Arman et al. (2018) A Landscape of Metabolic Variation across Tumor Types. Cell Syst 6:301-313.e3 |
| Huang, Justin K; Jia, Tongqiu; Carlin, Daniel E et al. (2018) pyNBS: a Python implementation for network-based stratification of tumor mutations. Bioinformatics 34:2859-2861 |
| MacParland, Sonya A; Liu, Jeff C; Ma, Xue-Zhong et al. (2018) Single cell RNA sequencing of human liver reveals distinct intrahepatic macrophage populations. Nat Commun 9:4383 |
| Pai, Shraddha; Bader, Gary D (2018) Patient Similarity Networks for Precision Medicine. J Mol Biol 430:2924-2938 |
| Ebhardt, H Alexander; Root, Alex; Liu, Yansheng et al. (2018) Systems pharmacology using mass spectrometry identifies critical response nodes in prostate cancer. NPJ Syst Biol Appl 4:26 |
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