Biomedical computing Michael Welge, Ian Brooks, Victor Jongeneel • Biomedicine identified as being of high importance to NCSA, but definition of strategic plan still in early stages • Expect to have a fully formed strategy by end 2010 • Overall process for developing a plan: • Understand the strengths of NCSA and be prepared to capitalize on them; identify weakness that need to be addressed • Define the overall areas of opportunity for high-performance computing in the biomedical area • Identify strategic partnerships on- and off-campus, with the potential to initiate projects congruent with the above • Engage in substantive discussions with partners and define the scope of common projects NCSA Strategic Planning Presentation (April 20, 2010)
Understanding the strengths of NCSA • Most relevant NCSA activities (View of NCSA): • • • High-performance data services (2) Science visualization for scientists and engineers (5) Cyber-applications for scientific and engineering communities (6) Security technologies and software (11) High-performance computing services (1) • Core competence in large-scale data mining • Handling and extracting information from massive datasets • Building on past successes • Continuing work on NAMD and its applications • NCSA seminal contribution to MIDAS (Models of Infectious Disease Agents Study) • Collaborative projects with IGB (e. g. Evolution Highway) • International and national disease monitoring and control NCSA Strategic Planning Presentation (April 20, 2010)
Defining areas of opportunity (from 2006 NSF workshop) • Biomolecular Structure Modeling (for example extending classical Molecular Dynamics calculations to account for quantum mechanical effects, multidimensional free energy surfaces, transition state ensembles) • Modeling Complex Biological Systems (for example developing models of cell and organ function) • Genomics (for example search calculations mapping phylogeny to ontogeny) • Customized Patient Care (for example computing drug interactions in the context of individual physiology and blood chemistry) • Ecological component of earth system modeling (for example adding plant cover to climate models) • Infectious disease modeling (for example modeling of disease spreading and the likely impact of containment strategies) NCSA Strategic Planning Presentation (April 20, 2010)
Information-based medicine MAYO CLINIC DIVISION OF BIOMEDICAL SCIENCES
Additional areas of opportunity • Data management solutions for high-throughput biology • “Next generation” sequencing currently generates tens of TB raw data per experiment, steep increases likely • Other technologies are also rapidly increasing output: proteomics with prior spatial and/or chemical separation, high-throughput high-resolution imaging, … • Understanding the relationship between genotype and phenotype • Rapidly increasing production of full genome sequences from individuals within one species (mostly human) and from different species; millions of differences observed, thousands of genomes being sequenced • Identifying genomic determinants of phenotypic differences is a major data mining / statistical problem NCSA Strategic Planning Presentation (April 20, 2010)
High-throughput biology - one recent example 190, 000 movies recording over 19 million cell divisions… NCSA Strategic Planning Presentation (April 20, 2010)
Data analysis and hit detection. B Neumann et al. Nature 464, 721 -727 (2010) doi: 10. 1038/nature 08869
A schema for implementing individualized medicine NCSA Strategic Planning Presentation (April 20, 2010)
Strategic Partnerships • On campus • IGB – medium-scale sequencing projects, comparative genomics, evolution • Beckman, Bioeng. – high-throughput imaging and analysis • Genomic Institute of Singapore • Existing collaboration with Ed Liu, institutional ties, immediate need for expertise • Mayo Clinic • Mo. U in place, unmatched patient records, committed to developing individualized medicine, poised to boost sequencing capability • Genome Center at Wash U • One of the pre-eminent genome centers worldwide • Faced with critical data management and analysis problems in spite of heavy investments • Possible new partnerships • Wellcome Trust Sanger Institute – where much of high-throughput biology is happening • EMBL/EBI, Broad Institute, BGI-Shenzhen, Genoscope, ? ? ? NCSA Strategic Planning Presentation (April 20, 2010)
Scope of projects (with partners) • Discussions are ongoing, nothing decided yet • Overall themes emerging: • Practical solutions for large-scale data management in the life sciences • Development of tools, including visualization, for comparative genomics (within or between species) • Data mining for personalized medicine – integration of “omic” data with phenotypic records • Disease prevention through monitoring and modeling • Real-time medical decision support • Needed soon: a WOW project highlighting the know-how and capabilities of NCSA Strategic Planning Presentation (April 20, 2010)
Sources • NSF Workshop Report: Petascale Computing in the Biological Sciences (2006) • Edited by Allan Snavely, Gwen Jacobs, and David A. Bader • Presentation from Division of Biomedical Sciences on “Information-based Medicine” • Discussion with Roberto Fabbretti, Jacques Rougemont, Ioannis Xenarios (Lausanne) on data needs of next-gen sequencing • Many discussions with faculty and staff from NCSA, IGB, Bioengineering, other UIUC Departments • Dozens of recent papers, particularly in Nature and Nature Genetics NCSA Strategic Planning Presentation (April 20, 2010)
Скачать презентацию Biomedical computing Michael Welge Ian Brooks Victor Jongeneel
7760794e35f7382143c450999272f623.ppt