The mission of the Center for the Multiscale Analysis of Genomic and Cellular Networks (MAGNet) is to develop novel Structural and Systems Biology methods and tools for the dissection of molecular interactions in the cell and for the interaction-based elucidation of cellular phenotypes. These tools are made freely available to the the members of the research community. They are also validated in the context of the Center's own research program through collaborative projects with experimental biologists. Several of these projects have already led to results of seminal nature, including for instance the elucidation of the role of DNA shape in protein-DNA binding specificity [Joshi et. al. 2007, Rohs et. al. 2009, Slattery et. al. 2011], the identification of the Master Regulators of the mesenchymal subtype of Glioblastoma [Carro et. al. 2009], and the discovery of an extensive microRNA-mediated regulatory network of RNA-RNA interactions in brain tumors [Sumazin et. al. 2011].
MAGNet is one of 8 National Centers for Biomedical Computing (NCBCs, http://www.ncbcs.org/). These Centers, in conjunction with individual investigator awards, are creating a networked effort to build the computational infrastructure for biomedical computing in the nation. The NCBC program is devoted to all facets of biomedical computing, from basic research in computational science to providing the tools and resources that biomedical and behavioral researchers need to do their work. In addition to carrying out fundamental research the NCBCs play a major role in educating and training researchers to engage in biomedical computing.
MAGNet is also one of 12 inter-disciplinary Centers for Cancer Systems Biology (CCSBs), a component of the National Cancer Institute's Integrative Cancer Biology Program. The CCSBs provide a core framework for applying systems biology approaches to cancer research through the development and implementation of computational models of processes relevant to cancer prevention, diagnostics and therapeutics. The CCSBs seek to integrate experimental biology with mathematical modeling to foster new insights in the biology and new approaches to the management of cancer.