An Endless Frontier_ Better Biology Through Information Technology

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An Endless Frontier: Enable Biology Through Information Technology • Biology 21 - the life science research of the 21st Century – is rich, and will become exceptionally rich, in diverse, complex data, while focusing on a system-level of understanding, enabling predictive capacity – The language for understanding biology at a systems level will be bioinformatics/IT as calculus/math has been the language for understanding the physical sciences – a compelling partnership at the frontier between IT and all of the biological sciences will be created • “Computing has changed biology forever; most biologists just don’t know it yet” – Michael Levitt • “Computational Biology is as essential for next Q Century as Molecular Biology was the last” – William McGinness 21st Century BIO-Cyberinfrastructure Changing How Science is Done Providing the Tools to Swim in the Rapid Current of Data “Computers” now KNOW about Biology Planetary Sciences Engineering CFD Earth Sciences Chemistry Industry Biomolecular Astronomy Materials Particle Physics 6/1/97 to 5/31/98 CTC, NCSA, PSC, SDSC Number Scale (over size scale from Angstroms to Km) Organisms 10 10 10 6 3 The Complexity of Biosystems Finite element models Discrete Automata models Evolutionary Processes 0 10 Cells 10 10 Biopolymers 6 Ecosystems and Epidemiology Organ function Electrostatic continuum models 3 Cell signalling 0 10 10 10 6 DNA replication Enzyme Mechanisms Protein Folding 3 Ab initio Quantum Chemistry 0 10 Atoms 10 10 6 Regions where Computational Modeling can be Employed Today vs Goals for Coverage Homology-based Protein modeling Empirical force field Molecular Dynamics First Principles Molecular Dynamics 3 0 10 -15 10 -12 10 -9 10 -6 10 -3 10 0 10 3 10 6 10 9 Time Scale (seconds) Geologic & Evolutionary Timescales Bioinformatics / IT for Life Science: Drinking from the Fire Hose in the Era of Data-rich, Genome-enabled Biology Dynamic Form and Function: Characterizing Biological Mechanisms Across Multiple Scales Genomes Gene Products   Structure & Function Pathways & Physiology   Populations & Evolution Ecosystems Scientific Challenges Data Integration Challenges Computational Challenges Algorithmic Challenges Crosscutting Themes Underlying Major IT Challenges for Genomeenabled Biological Science • Specifying the Relationships of Molecular Sequence, Structure and Function • Bridging Vast Scales of Time, Space and Biological Organization • Understanding the Complexity of Living Systems [Summary, NSF BIO computing workshop] Exemplar Research Challenges in the Life Sciences that require BIO Cyberinfrastructure 1. Full genome-genome comparisons 2. Rapid assessment of polymorphic genetic variations 3. Complete construction of orthologous and paralogous groups of genes 4. Structure determination of large macromolecular assemblies/complexes 5. Dynamical simulation of realistic oligomeric systems 6. Rapid structural/topological clustering of proteins, families 7. Prediction of unknown molecular structures; protein folding 8. Computer simulation of membrane structure and dynamic function 9. Simulation of genetic networks including the sensitivity of these pathways to component stoichiometry and kinetics 10. Integration of observations across scales of vastly different dimensions and organization to yield realistic, ecological and environmental models for basic biology and societal needs Model Exists: Architecture To Support a Biological Informatics Research Network BIRN - Phase I - 2001-2002 UCSD NIH Centers for Bio Imaging and Computational Biology & NCRR Research Ctrs. Form a National Scale Data Grid and Federate Multi-scale NeuroImaging Data from Centers with High Field MRI and Advanced 3D Microscopes Harvard Cal Tech NSF NPACI W/SDSC Cal-(IT)2 UCLA “Deep Web” Duke Integrating Cyber Infrastructure to Link: •Advanced Imaging Instruments •Data Intensive Computing •Multi-Scale Brain Databases Test Beds for an NSF BIO Cyberinfrastructure Sites National-Scale, Testbed in Cyberinfrastructure: Federating Multi-Scale, Multi-Modal NeuroImaging Data Could Expand Readily; Examples: Plant & Microbe Genome, Cellular Level; Tree of Life; also Indefinite Expansion to Many Laboratories Model-based Integration of Multi-resolution Data: Development of a Cell Centered Database Parallel computing resources for tomography Spatial database of rat brain anatomy Models Neuronal models Database federation Imaging databases Large scale 3D EM reconstructions Cells and tissues Modeling cellular microdomains Cellular processes Cellular microdomains BIRN IT System Maryann Martone Macromolecular distributions Correlated LM and EM Amarnath Gupta Bertram Ludaescher Hi-throughput tomography BIRN Information Integration What is the cerebellar distribution of rat proteins with more than 70% homology with human NCS-1? Integrated View Integrated View Definition Mediator Wrapper Wrapper Wrapper Wrapper Web protein localization morphometry neurotransmission CaBP, Expasy PDB & Genome enabled Biology – Using Structure to Understand Function Accelerated Drug Development Individualized Medicine Productive, Healthy Citizens Environmental Remediation Biofuels, Biocatalysts Improved Agriculture DNA Sequence Implies Structure Implies Function DNA Sequence Provides Protein Sequence CA Synchrotron Facilities Provide 3-D Protein Structure Basis for 21st Century Medicine, Sustainable Development: Enhanced U.S. Competitiveness, Environmental Quality A Cyberinfrastructure for BIO is Needed to Extract Implicit Genome Information PDB Status:Numbers and Complexity (a) myoglobin (b) hemoglobin (c) lysozyme (d) transfer RNA (e) antibodies (f) viruses (g) actin (h) the nucleosome (i) myosin (j) ribosome David Goodsell, TSRI A Cyberinfrastructure for Century Biological Sciences st 21 • All BIO research endeavors will require this Foundation – open access, opportunities. • BIO should define the Architecture, initiate construction, at Highest Priority. • Create Test beds modeled on BIRN, GryPhyn; describe LTER, NEON options. • BIO scientists will extend the framework in exciting ways beyond expectation. Obvious Opportunities: Early BIO Test Bed Options • • • • • • • • • • • • Interconnecting Extant Database Activities Evo-Devo/Devo-Evo; Networks; Phylogeny Systems Biology Plant Genomes Microbial Genome Sequencing Ecology of Infectious Diseases Tree of Life LTER Biocomplexity in the Environment NEON Frontiers in Integrative Biological Research Research Coordination Networks

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