The Dissemination component of the National Resource for Network Biology (NRNB) aims to share as broadly as possible the new analytical methods, software, and other bioinformatic resources being developed in our technology research and development projects.
This aim i s aligned with the overall mission of the NRNB to bring cutting-edge technologies to bear on biomedical research problems. Our dissemination strategy has two themes: informing the scientific community about the technologies and accomplishments of the NRNB, and promoting and enabling the broader use of these technologies. These themes run through our varied dissemination activities: conferences and workshops, online community outreach, hosted websites and web services, publishing, resource sharing and competitions. The following is a summary of the progress and measurable impact of our dissemination efforts so far: 83 publications citing the NRNB grant during our first four years Over 400 participants per year at NRNB-hosted conferences Over 250 members of the NRNB-moderated Network Biology LinkedIn Group Active Cytoscape mailing list: 282 new posts on 80 different topics in a typical month Average of 1,100 visits to NRNB.org per month Top Google hit when searching for network biology tools or network biology resources 17 network biology tools supported or maintained by NRNB Average of 5,400 visits per month to NRNB tutorials site Over 35 Cytoscape-related tutorials available at NRNB tutorial site Average of 9,500 visits per month to NRNB-built and -maintained Cytoscape App Store 340 downloads per day from NRNB's Cytoscape App Store In the next support period, we will continue to push forward all of these efforts, in addition to pursuing: DREAM Challenges for the Network Biology community New Cytoscape App Store features Improved integration of App Store, Tutorials and Cytoscape website Increased outreach to new communities of biomedical researchers and clinicians
| 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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