Collaborations Between Calit2, SIO, and the Venter Institute-a Beginning


Published on

Talk to the Venter Institute Board
Title: Collaborations Between Calit2, SIO, and the Venter Institute-a Beginning
La Jolla, CA

Published in: Technology
  • Be the first to comment

  • Be the first to like this

No Downloads
Total views
On SlideShare
From Embeds
Number of Embeds
Embeds 0
No embeds

No notes for slide
  • Biology driven Science has top priority Infrastructure support Portable solution package Balance technology development and scientific discovery Mix production software and new technology framework Productive and future proof APBS image: CCMV capsid electrostatic potential mapped on the solvent-accessible molecular surface Zhang, D., R. Konecny, N.A. Baker, J.A. McCammon. Electrostatic Interaction between RNA and Protein Capsid in CCMV Simulated by a Coarse-grain RNA model and a Monte Carlo Approach. Biopolymers, 75(4), 325-337 (2004). [ link ] Abstract: Although many viruses have been crystallized and the protein capsid structures have been determined by x-ray crystallography, the nucleic acids often cannot be resolved. This is especially true for RNA viruses. The lack of information about the conformation of DNA/RNA greatly hinders our understanding of the assembly mechanism of various viruses. Here we combine a coarse-grain model and a Monte Carlo method to simulate the distribution of viral RNA inside the capsid of cowpea chlorotic mottle virus. Our results show that there is very strong interaction between the N-terminal residues of the capsid proteins, which are highly positive charged, and the viral RNA. Without these residues, the binding energy disfavors the binding of RNA by the capsid. The RNA forms a shell close to the capsid with the highest densities associated with the capsid dimers. These high-density regions are connected to each other in the shape of a continuous net of triangles. The overall icosahedral shape of the net overlaps with the capsid subunit icosahedral organization. Medium density of RNA is found under the pentamers of the capsid. These findings are consistent with experimental observations. Figure 3. The electrostatic potential mapped on the solvent-accessible molecular surface of the capsid viewed from outside (a) and inside (b). The color bar is the same for both images. GAMESS/QMView Lepitopterene Molecule Autodock: Andy’s lab new paper using APBS, Autodock in J. Med. Chem. 2004. Nonhomogeneous Epicardial Strain Measurements of Anterior LV During Acute Myocardial Ischemia
  • Collaborations Between Calit2, SIO, and the Venter Institute-a Beginning

    1. 1. “ Collaborations Between Calit2, SIO, and the Venter Institute—a Beginning " Talk to the Venter Institute Board La Jolla, CA December 5, 2005 Dr. Larry Smarr Director, California Institute for Telecommunications and Information Technology; Harry E. Gruber Professor, Dept. of Computer Science and Engineering Jacobs School of Engineering, UCSD
    2. 2. Driving Cyberinfrastructure with Environmental Metagenomics Samples Collected by Sorcerer II How did Calit2, SIO, and VI Arrive at This Unified Vision? Funded Today! $24. 5 M Over 7 Years J. Craig Venter, et al. Science 2 April 2004: Vol. 304. pp. 66 - 74
    3. 3. Metagenomics “Extreme Assembly” Requires Large Amount of Pixel Real Estate Source: Karin Remington J. Craig Venter Institute Prochlorococcus Microbacterium Burkholderia Rhodobacter SAR-86 unknown unknown
    4. 4. Metagenomics Requires a Global View of Data and the Ability to Zoom Into Detail Interactively Overlay of Metagenomics Data onto Sequenced Reference Genomes (This Image: Prochloroccocus marinus MED4) Source: Karin Remington J. Craig Venter Institute
    5. 5. The OptIPuter – Creating High Resolution Portals Over Dedicated Optical Channels to Global Science Data Green: Purkinje Cells Red: Glial Cells Light Blue: Nuclear DNA Source: Mark Ellisman, David Lee, Jason Leigh 300 MPixel Image! Calit2 (UCSD, UCI) and UIC Lead Campuses—Larry Smarr PI Partners: SDSC, USC, SDSU, NW, TA&M, UvA, SARA, KISTI, AIST
    6. 6. Scalable Displays Allow Both Global Content and Fine Detail Source: Mark Ellisman, David Lee, Jason Leigh 30 MPixel SunScreen Display Driven by a 20-node Sun Opteron Visualization Cluster
    7. 7. Allows for Interactive Zooming from Cerebellum to Individual Neurons Source: Mark Ellisman, David Lee, Jason Leigh
    8. 8. Why Optical Networks Will Become the 21 st Century Driver Scientific American, January 2001 Number of Years 0 1 2 3 4 5 Performance per Dollar Spent Data Storage (bits per square inch) (Doubling time 12 Months) Optical Fiber (bits per second) (Doubling time 9 Months) Silicon Computer Chips (Number of Transistors) (Doubling time 18 Months)
    9. 9. Challenge: Average Throughput of NASA Data Products to End User is Only < 50 Megabits/s Tested from GSFC-ICESAT January 2005
    10. 10. Solution: Individual 1 or 10Gbps Lightpaths -- “Lambdas on Demand” ( WDM) Source: Steve Wallach, Chiaro Networks “ Lambdas”
    11. 11. National Lambda Rail (NLR) and TeraGrid Provides Cyberinfrastructure Backbone for U.S. Researchers San Francisco Pittsburgh Cleveland San Diego Los Angeles Portland Seattle Pensacola Baton Rouge Houston San Antonio Las Cruces / El Paso Phoenix New York City Washington, DC Raleigh Jacksonville Dallas Tulsa Atlanta Kansas City Denver Ogden/ Salt Lake City Boise Albuquerque UC-TeraGrid UIC/NW-Starlight Chicago International Collaborators NLR 4 x 10Gb Lambdas Initially Capable of 40 x 10Gb wavelengths at Buildout NSF’s TeraGrid Has 4 x 10Gb Lambda Backbone Links Two Dozen State and Regional Optical Networks DOE, NSF, & NASA Using NLR
    12. 12. Extending Telepresence with Remote Interactive Analysis of Data Over NLR SIO/UCSD NASA Goddard August 8, 2005 HDTV Over Lambda OptIPuter Visualized Data 25 Miles Venter Institute
    13. 13. First Trans-Pacific Super High Definition Telepresence Meeting in New Calit2 Digital Cinema Auditorium Sony NTT SGI Lays Technical Basis for Global Scientific Collaboration Keio University President Anzai UCSD Chancellor Fox
    14. 14. <ul><li>September 26-30, 2005 </li></ul><ul><li>Calit2 @ University of California, San Diego </li></ul><ul><li>California Institute for Telecommunications and Information Technology </li></ul>Calit2@UCSD Is Connected to the World at 10,000 Mbps T H E G L O B A L L A M B D A I N T E G R A T E D F A C I L I T Y Maxine Brown, Tom DeFanti, Co-Chairs 50 Demonstrations, 20 Counties, 10 Gbps/Demo i Grid 2005
    15. 15. Calit2 is Partnering with SIO to Prototype a Digital Environment Research Systems <ul><li>Viewing and Analyzing Earth Satellite Data Sets </li></ul><ul><li>Earth Topography </li></ul><ul><li>Atmospheric Brown Clouds </li></ul><ul><li>Climate Modeling </li></ul><ul><li>Surface, Subsurface, and Ocean Floor Observatories </li></ul><ul><li>Coastal Zone Data Assimilation </li></ul><ul><li>Ocean Environmental Metagenomics </li></ul>John Orcutt, Director CEOA Deputy Director, SIO Smarr March 2005 Talk to SIO Council Led to Calit2 Discussions with Craig Venter
    16. 16. First Remote Interactive High Definition Video Exploration of Deep Sea Vents Source John Delaney & Deborah Kelley, UWash Canadian-U.S. Collaboration
    17. 17. A Near Future Metagenomics Fiber Optic-Enabled Data Generator Source John Delaney, UWash
    18. 18. Use SCCOOS As Prototype for Coastal Zone Data Assimilation Testbed Goal: Link SCCOOS Sites with LambdaGrid to Prototype Future Ocean and Earth Sciences Observing System Yellow—Proposed Initial Lambda Backbone
    19. 19. Use OptIPuter to Couple Data Assimilation Models to Remote Data Sources Including Biology Regional Ocean Modeling System (ROMS) NASA MODIS Mean Primary Productivity for April 2001 in California Current System
    20. 20. Marine Microbial Metagenomics From Species Genomes to Ecological Genomes <ul><li>Each Sequence is a Part of an Entire Biological Community </li></ul><ul><li>Sequences, Genes and Gene Families, Coupled With Environmental Metadata </li></ul><ul><ul><li>Tremendous Potential to Better Understand the Functioning of Natural Ecosystems </li></ul></ul><ul><li>Challenge </li></ul><ul><ul><li>Much More Powerful Information Infrastructure Required to Support Metagenomics </li></ul></ul>Scripps Genome Center Dr. Terry Gaasterland
    21. 21. Evolution is the Principle of Biological Systems: Most of Evolutionary Time Was in the Microbial World Source: Carl Woese, et al You Are Here Much of Genome Work Has Occurred in Animals
    22. 22. Comparative Genomics Can Reveal Biological Facts That Are Not Visible Within a Species “ After sequencing these three genomes, it is clear that substantial rearrangements in the human genome happen only once in a million years, while the rate of rearrangements in the rat and mouse is much faster.” --Glenn Tesler, UCSD Dept. of Mathematics Co-Authors Pavel Pevzner and Glenn Tesler, UCSD April 1, 2004 December 05, 2002 December 9, 2004
    23. 23. Advanced Algorithmic Techniques Reveal Unexpected Results “ Many of the chicken–human aligned, non-coding sequences occur far from genes, frequently in clusters that seem to be under selection for functions that are not yet understood.” Nature 432, 695 - 716 (09 December 2004)
    24. 24. Calit2 Researcher Eskin Collaborates with Perlegen Sciences on Map of Human Genetic Variation Across Populations David A. Hinds, Laura L. Stuve, Geoffrey B. Nilsen, Eran Halperin, Eleazar Eskin , Dennis G. Ballinger, Kelly A. Frazer, David R. Cox. “ Whole-Genome Patterns of Common DNA Variation in Three Human Populations” Science 18 February, 2005: 307(5712):1072-1079. “ We have characterized whole-genome patterns of common human DNA variation by genotyping 1,586,383 single-nucleotide polymorphisms (SNPs) in 71 Americans of European, African, and Asian ancestry.” “ Although knowledge of a single genetic risk factor can seldom be used to predict the treatment outcome of a common disease, knowledge of a large fraction of all the major genetic risk factors contributing to a treatment response or common disease could have immediate utility, allowing existing treatment options to be matched to individual patients without requiring additional knowledge of the mechanisms by which the genetic differences lead to different outcomes .” “ More detailed haplotype analysis results are available at “
    25. 25. The Bioinformatics Core of the Joint Center for Structural Genomics will be Housed in the Calit2@UCSD Building Extremely Thermostable -- Useful for Many Industrial Processes (e.g. Chemical and Food) 173 Structures (122 from JCSG) <ul><ul><li>Determining the Protein Structures of the Thermotoga Maritima Genome </li></ul></ul><ul><ul><li>122 T.M. Structures Solved by JCSG (75 Unique In The PDB) </li></ul></ul><ul><ul><li>Direct Structural Coverage of 25% of the Expressed Soluble Proteins </li></ul></ul><ul><ul><li>Probably Represents the Highest Structural Coverage of Any Organism </li></ul></ul>Source: John Wooley, UCSD
    26. 26. Providing Integrated Grid Software and Infrastructure for Multi-Scale BioModeling Web Portal Rich Clients Telescience Portal Grid Middleware and Web Services Workflow Middleware PMV ADT Vision Continuity APBSCommand Located in Calit2@UCSD Building Grid and Cluster Computing Applications Infrastructure Rocks Grid of Clusters APBS Continuity Gtomo2 TxBR Autodock GAMESS QMView National Biomedical Computation Resource an NIH supported resource center
    27. 27. Calit2 Intends to Jump Beyond Traditional Web-Accessible Databases Data Backend (DB, Files) W E B PORTAL (pre-filtered, queries metadata) Response Request + many others Source: Phil Papadopoulos, SDSC, Calit2 BIRN PDB NCBI Genbank
    28. 28. Calit2’s Direct Access Core Architecture Will Create Next Generation Metagenomics Server Traditional User Response Request Source: Phil Papadopoulos, SDSC, Calit2 + Web Services Flat File Server Farm W E B PORTAL Dedicated Compute Farm (100s of CPUs) TeraGrid: Cyberinfrastructure Backplane (scheduled activities, e.g. all by all comparison) (10000s of CPUs) Web (other service) Local Cluster Local Environment Direct Access Lambda Cnxns OptIPuter Cluster Cloud Data- Base Farm 10 GigE Fabric
    29. 29. What Will Our Core Data Sets Be? <ul><li>Metagenomic </li></ul><ul><ul><li>Sargasso Sea + Sorcerer II Expedition (GOS) </li></ul></ul><ul><ul><li>JGI Community Sequencing Project </li></ul></ul><ul><li>Microbial Genomes </li></ul><ul><ul><li>Moore Marine Microbial Project </li></ul></ul><ul><ul><li>JGI Community Sequencing Project </li></ul></ul><ul><ul><li>Other Relevant genomes (e.g., from Genbank) </li></ul></ul><ul><li>Standard </li></ul><ul><ul><li>Non-Redundant Nucleotide and AA Databases </li></ul></ul><ul><li>Environmental and Satellite data </li></ul><ul><ul><li>NOAA Oceans and NASA Goddard Satellite Date </li></ul></ul>Source: Saul Kravitz Director of Software Engineering J. Craig Venter Institute
    30. 30. Looking Back Nearly 4 Billion Years In the Evolution of Microbe Genomics Science Falkowski and Vargas 304 (5667): 58