Cyberinfrastructure Day 2010: Applications in Biocomputing
Upcoming SlideShare
Loading in...5
×
 

Cyberinfrastructure Day 2010: Applications in Biocomputing

on

  • 1,016 views

UNM Cyberinfrastructure Day 2010 presentation: Applications in Biocomputing, biomedical and cheminformatics research computing cyberinfrastructure issues.

UNM Cyberinfrastructure Day 2010 presentation: Applications in Biocomputing, biomedical and cheminformatics research computing cyberinfrastructure issues.

Statistics

Views

Total Views
1,016
Views on SlideShare
1,012
Embed Views
4

Actions

Likes
1
Downloads
28
Comments
0

2 Embeds 4

http://www.lmodules.com 2
http://www.linkedin.com 2

Accessibility

Categories

Upload Details

Uploaded via as Adobe PDF

Usage Rights

© All Rights Reserved

Report content

Flagged as inappropriate Flag as inappropriate
Flag as inappropriate

Select your reason for flagging this presentation as inappropriate.

Cancel
  • Full Name Full Name Comment goes here.
    Are you sure you want to
    Your message goes here
    Processing…
Post Comment
Edit your comment

Cyberinfrastructure Day 2010: Applications in Biocomputing Cyberinfrastructure Day 2010: Applications in Biocomputing Presentation Transcript

  • Jeremy Yang Software Systems Manager Division of Biocomputing Dept. of Biochemistry & Molecular Biology UNM School of Medicine Cyberinfrastructure Day -- April 22, 2010
  • I. What is Biocomputing? II. Cyber Revolution (~1980-2010+) III. Cyberinfrastructure (To be or not to be?) IV. Super Computing, Redefined
  • Division of Biocomputing http://biocomp.health.unm.edu/ Department of Biochemistry & Molecular Biology School of Medicine Also affiliated with the NIH Roadmap-funded UNM Center for Molecular Discovery
  •   Biomolecular screening  Data mining, machine informatics learning   Cheminformatics   3D visualization   Bioinformatics   Public data integration   Genomics   Collaborations in   Virtual screening chemistry, biology, medicine, comp sci   Molecular modeling   BIOMED 505 course   SAR (Structure- Activity-Relationship)   Software development, management, deployment & support
  • Larry Sklar, et al., UNMCMD (NIH Roadmap) ~$20M NIH awarded to date
  •  32 cpu Linux cluster  2+ Oracle instances  32GB RAM server  PostgreSQL, MySQL  Linux: OpenSUSE, CentOS,  Stereo graphics RedHat, Fedora, Ubuntu workstation  SGI/IRIX  25+ scientific software  Windows, Mac OS X packages  Automated integration with  Supported in-house NIH databases applications We are cyberinfrastructure users and providers!
  • Virtual chemistry; property prediction, chemspace navigation, computer aided molecular design, graph theory, databases
  •  Nucleotide and protein sequence analysis  Genomics, proteomics  Merging with chemical biology, etc.
  •  Computational search for likely biological actives Example: 3D shape search;  Database may be real or virtual prozac & paxil compounds  2D and 3D methods  2D similarity search  3D similarity search (shape, pharmacophore)  docking (3D, protein binding site) c/o OpenEye Rocs
  • atoms, bonds, surfaces, fields, interactions, stereo serotonin hemoglobin
  • Computational models for protein-ligand binding Abl kinase (1iep.pdb)‫‏‬ interaction potentia hydrophobic (green hbond acceptors (r Gleevec in binding site Gleevec is a leukemia drug known to bind with Abl kinase.
  • (Watch movies...) PyMol movie: http://video.google.com/videoplay? docid=-5859274887925224981# Jmol interactive DNA modeling demo: http://chemapps.stolaf.edu/pe/protexpl/htm/top.htm? id=1d66&&&chpa=true Expert users can advance understanding via rich, dynamic, visual interfaces.
  • E.g., Searching NIH PubChem for non-selectivity
  • Many biomedical data sources worldwide SLIDE 15 (15 MIN?)
  • Division of Biocomputing in 2008
  •  Rapid change, challenge and opportunity  Learning from history, trends (new not enough)  Winners and losers  Science, experts have led and followed.  ~1980-2010 covers 3σ (99.7%)  And evolution...
  •  Rapid change, challenge and opportunity  Learning from history, trends  Winners and losers  Science, experts have led and followed.  ~1980-2010 covers 3σ (99.7%)  And evolution...
  • 1977: Atari 2600 1978: Space Invaders 1981: IBM-PC (MS-DOS) 1983: cellphone 1983: GNU Project 1984: Neuromancer, William Gibson, “cyberspace” 1984: Apple Mac, mouse, windows & icons
  • 1985: Oracle 5 (client-server) 1989: Intel 486 Pentium (1M transistors, 50MHz) 1990: MS Windows 3.0 1990: WWW (Berners-Lee) 1991: High Perf Comp & Comm Act (Al Gore) 1991: Linux (Linux Torvalds) 1991: AOL 1991: ETrade
  • 1993: Jurassic Park (via SGI) 1993: NCSA Mosaic 1994: Netscape Navigator 1994: “Good Times” hoax 1994: Match.com 1995: “Concept” virus (Word) 1995: Internet Explorer 1995: Apache project 1995: Yahoo!
  • 1995: Amazon.com 1995: My mother gets email 1997: Google 1997: eBay 1999: Melissa virus (Outlook) 1999: Napster (p2p) 2000: MS convicted 2000: 3M USA broadband* 2000: dot-com bubble pops *Fixed non dial-up internet connections >56k (FCC).
  • 2000: 802.11b wireless 2001: Apple iPod 2001: Apple iTunes 2001: Wikipedia 2003: Skype 2005: YouTube 2005: Rio power grid hacked 2005: NSA domestic surveillance 2006: Facebook
  • 2006: Amazon Cloud 2007: DOD hacked 2008: 70M USA broadband* 2009: Cyberdefense USA priority 2009: Twitter role in Iran election protests 2010: UAVs are SOPs 2011: Cyber terrorism? *Fixed non dial-up internet connections >56k (FCC).
  • The dotted line keeps moving... Case study: database cheminformatics in pharma research, 1990→2000.
  •  In 1990, high speed chemical searching was beyond standard capabilities.  Research groups managed local servers in their labs & specialized DB engines (e.g. Daylight Inc.).  By 2000, this function had moved to IT (via Oracle cartridges, etc.) corporate informatics infrastructure  Transition not smooth, but very beneficial.
  • Standard cocaine functions: substructure, similarity, identity chemical searching imidazoles
  • (1) office equipment (2) lab equipment (3) experimental apparatus (4) the experiment (5) a commodity (6) custom configured experimental vehicle for exploration (5) all of the above
  • (1) office equipment (2) lab equipment (3) experimental apparatus (4) the experiment (5) a commodity (6) custom configured experimental vehicle for exploration (5) all of the above
  •  Scientific software  Computational science  Commodity software  Engineering enables science  Science requires agile development, high performance, experimentation, risk taking, play.  Cyberinfrastructure users and developers/maintainers SLIDE 30 (30 MIN?)
  •  Scientific research  Scientific software for experts  Computational research  Enabling software for  High performance scientists computing as a research tool  Commoditization (e.g. cloud computing)  High performance infrastructure as a  Plumbing vs. productivity tool experimental apparatus  Appropriate tiers and domains
  • IT: “Poorly managed Research: “We need computers and needy ill- power, flexibility and trained users put the access and not another system at risk.” lame PC.”
  • And with other cyberfolks too. And with great results.
  •  In ~5 yrs, super → un-super  Super computing? Define computer.  Advances from unexpected places:   gaming, movies (graphics -- vs. AI)   social networking (crowdsourcing)   even business (web standards, UIs, security)  Super computing is pushing the current limits  But where are the key frontiers?
  • Advances from unexpected places...
  • Colossus code breaking computer, UK.
  • Eniac computer, Univ of Pennsylvania.
  • Cray computer
  • SLIDE 40 (40 MIN?)
  • High performance (super) computing is pushing the current limits.
  • This is what a “computer” looks like.
  • “The network is the computer.” - John Gage (Sun, NetDay founder)
  • Corollaries:  The network is the (semantic) database  The network is cyberspace  The network is us too
  •  Super users → super computing  Blackbox AI/monolith paradigm limiting  Human/computer co-evolution Cytoscape biological network visualizer with drug - target interactions
  • “Super Computers” @ Division of Biocomputing  Tudor Oprea  Cristian Bologa  Stephen Mathias  Oleg Ursu Happy Earth Day!  Jerome Abear  Ramona Curpan  Liliana Halip Jeremy Yang  Andrei Leitao jjyang@salud.unm.edu Cyberinfrastructure Day -- April 22, 2010