National Center: Multiscale Analysis of Genomic and Cellular Networks (MAGNet)
Project Number5U54CA121852-08
Contact PI/Project LeaderCALIFANO, ANDREA
Awardee OrganizationCOLUMBIA UNIVERSITY HEALTH SCIENCES
Description
Abstract Text
In this document we outline our proposal for the renewal of our Center for the Multiscale Analysis of Genetic
Networks (MAGNet). Over the last funding period ('05-'10), the MAGNet Center has made major progress in
the description of molecular interactions involving proteins and DNA, in their functional analysis within specific
cellular contexts, and in using this information to elucidate mechanisms controlling physiological and
pathological phenotypes. As documented in this proposal, MAGNet has a compelling publication record, has
made important discoveries across multiple scales of biological and disease related processes, and has
developed key algorithms, models, and software that have been broadly adopted by the biomedical research
community.
We now plan fundamentally new research directions in multiple areas while, in parallel, achieving full
integration of our core Structural Biology and Systems Biology themes. Indeed, as discussed in the proposal,
these themes are highly synergistic and in combination can help dissect the relationship between atomic level
changes (genetic variability) and cellular changes (phenotypic variability), with obvious applications to the
elucidation of causal mechanisms in human disease. Center activities will involve a significant,
multidisciplinary effort that will tackle multiscale problems, ranging from the atomic-level modeling of protein
interaction specificity, to the reverse engineering of multi-layer regulatory networks, to using these models for
the interpretation of the role of genetic variability in determining cellular phenotypes. These activities will
directly impact three Driving Biological Projects aimed at (a) studying the DNA-binding specificity of key
developmental transcription factors (Hox proteins), (b) modeling ErbB signaling pathways in oncogenic
contexts using multi-factorial data and (c) assembling the first in vivo, genome-wide, regulatory network for
prostate cancer using molecular profiles from chemical perturbation of human xenografts.
While pursuing its tradition of scientific excellence, the center will continue to play a prominent role in the
dissemination of the tools, models, data, and algorithms developed by its investigators. This will be
accomplished primarily through geWorkbench, MAGNet's integrative bioinformatics platform, which has
matured into a highly compelling and heavily used tool, as shown by its endorsement by caBIG and by its
integration with other leading software tools such as GenePattern, Cytoscape, and Bioconductor. MAGNet will
also play a key role in the continued development of our advanced data center, which provides our
investigators with access to unique computational facilities and thus facilitates significant progress on research
problems that would otherwise be inaccessible.
Through MAGNet, we will further improve and extend the educational activities started in the previous funding
period, which have produced a truly integrated experimental-computational curriculum. We will also explore a
variety of options for dissemination of Center results and for the organization of community-based events, such
as the now very successful DREAM and RECOMB Systems Biology conferences. Finally, MAGNet has played
a central role in the development of an inter-disciplinary program in Computational Biology at Columbia
University that spans two campuses and seven academic departments. We believe that the unique research
environment we have created can serve as a model for the full integration of Computational Biology in all areas
of biomedical research.
Public Health Relevance Statement
Systems and Structural Biology are emerging as key complementary disciplines that can help guide our efforts
in the study of human disease. MAGNet has achieved a leadership role within the community in providing
tools, methodologies, and data that can be used by the research community at large to dissect complex
biological and disease related traits. Additionally, through its infrastructure, we will continue to support a large
number of NIH funded scientific collaborations that benefit other large research organization such as National
Cancer Centers and CTSA centers. Finally, our effort to create a truly integrated experimental-computational
educational curriculum is poised to produce the successful biologists of tomorrow, who will be equally
conversant in both disciplines.
NIH Spending Category
No NIH Spending Category available.
Project Terms
AdoptedAlgorithmsAreaAutomobile DrivingBindingBioconductorBioinformaticsBiologicalBiomedical ResearchCancer CenterChemicalsCollaborationsCommunitiesComplexComputational BiologyComputer softwareDNADNA BindingDataDevelopmentDisciplineDiseaseEducational ActivitiesEducational CurriculumEngineeringEnvironmentEventFundingGeneticGenomicsHumanLeadershipMalignant neoplasm of prostateMethodologyModelingMolecular ProfilingMutationOncogenicPhenotypePhysiologicalPlayProcessProteinsPublicationsResearchResearch InfrastructureResearch PersonnelRoleSignal PathwaySoftware ToolsSpecificitySystemSystems BiologyUnited States National Institutes of HealthUniversitiesXenograft procedurebasecancer Biomedical Informatics Gridcommunity organizationsdata modelingdocument outlinesgenetic analysisgenome-widehuman diseaseimprovedin vivomultidisciplinaryprogramsstructural biologysymposiumtooltraittranscription factor
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Publications
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