1. Overview of the Encyclopedia of Life (EOL) Project

2. Background Biology has become a data driven science
We have the blueprint (genomes) of over 800 organisms
This number will increase rapidly to the point in 5-10 years where your blueprint becomes a tool in your medical diagnosis
First we must understand the buildings (proteins) that control life’s processes
EOL strives to be the 21st century “Britannica” that everyone will turn to

3. EOL Project Description
The Encyclopedia of Life is a joint development of the San Diego Supercomputer Center (SDSC) and scientists and biological resources worldwide
EOL involves SDSC staff from HPC, DAKS, Grids and clusters and visualization
EOL has three parts:
1. Putative functional and 3-D structure assignment
through the largest computation ever attempted
2. True API level integration with key biological resources
3. A focus for future collaborative developments via the EOL Notebook

4. Type of Questions to be Addressed by EOL
If a knockout gene in arabidopsis leads to an average phenotypic response of 10% increased growth, will the same likely happen in rice?
Is protein X found in anthrax?
Is protein X a drug target, that is, does it exist predominantly in pathogenic bacteria of is it found in eukaryotes also?
Has caspase-1, a protein involved in cell death and aging been identified in any plants, if so what species and do the proposed protein structures look similar?
Give me all available information on caspase-1

5. EOL Basic Topology Genomic Data Putative Functional and 3D Assignment
Integration with Other Resources
Public and Private Databases
To Serve Thousands Worldwide

6. TeraGrid Some Technical Detail Mapped to the Topology
Sequence data from genomic sequencing projects
Ported applications
Load/update scripts
MySQL DataMart(s)
Pipeline data
Data warehouse
Structure assignment by PSI-BLAST
Structure assignment by 123D
Domain location prediction
Normalized DB2 schema
Application Server
Web/SOAP Server
Some Technical Detail
Mapped to the Topology
Retrieve Web pages & Invoke SOAP methods

7. One Plant Genome Processed as a Prototype
One Plant Genome Processed as a Prototype

8. Current Genomic Pipeline
Arabidopsis Protein sequences
sequence info
structure info
NR, PFAM
Prediction of :
signal peptides (SignalP, PSORT)
transmembrane (TMHMM, PSORT)
coiled coils (COILS)
low complexity regions (SEG)
SCOP, PDB
Building FOLDLIB:
PDB chains
SCOP domains
PDP domains
CE matches PDB vs. SCOP
90% sequence non-identical
minimum size 25 aa
coverage (90%, gaps <30, ends<30)
Create PSI-BLAST profiles for Protein sequences
Structural assignment of domains by PSI-BLAST on FOLDLIB
Only sequences w/out A-prediction
Structural assignment of domains by 123D on FOLDLIB
Only sequences w/out A-prediction
Functional assignment by PFAM, NR,
PSIPred assignments
Domain location prediction by sequence
FOLDLIB
Store assigned regions in the DB

9. Scale of Multi-genome Analysis
~800 10k-20k per =~107 ORF’s
Genomes Protein sequences
sequence info
structure info
NR, PFAM
Prediction of :
signal peptides (SignalP, PSORT)
transmembrane (TMHMM, PSORT)
coiled coils (COILS)
low complexity regions (SEG)
SCOP, PDB
4 CPU years
Building FOLDLIB:
PDB chains
SCOP domains
PDP domains
CE matches PDB vs. SCOP
90% sequence non-identical
minimum size 25 aa
coverage (90%, gaps <30, ends<30)
104 entries
228 CPU years
Create PSI-BLAST profiles for Protein sequences
Structural assignment of domains by PSI-BLAST on FOLDLIB
3 CPU years
Only sequences w/out A-prediction
Structural assignment of domains by 123D on FOLDLIB
9 CPU years
Only sequences w/out A-prediction
252 CPU years
Functional assignment by PFAM, NR,
PSIPred assignments
3 CPU years
Domain location prediction by sequence
FOLDLIB
Store assigned regions in the DB

10. TeraGrid application Technical aspects:
Excellent charter application for the TeraGrid project!
Good demonstration of producing practical output from TeraGrid computing: scientific papers and an extensive web site and services will be produced
Software pipeline now a proven technique and a sure bet
Can be implemented in the fastest possible time; project already initialized

11. EOL Data Services WWW MySQL DataMart(s) Data warehouse Pipeline data
Load/update scripts
Data warehouse
MySQL DataMart(s)
Pipeline data
Structure assignment by PSI-BLAST
Structure assignment by 123D
Domain location prediction
Publish Web Services & API
Application server
SOAP/Web Server
UDDI directory
Web pages served via JSP
EOL Notebook
Data incorporated into third party web pages
Automated data downloads to mirrors and researchers
Encyclopedia of Life
WWW

12. Basic Web Interface MS Internet Explorer Netscape 4.7/6.1 Mozilla v1.0
Opera
Microsoft Windows
Encyclopedia of Life
MS Internet Explorer
Netscape 4.7/6.1
Mozilla v1.0
Opera
Apple Macintosh
Netscape 4.7/6.1
Mozilla v1.0
Opera
Linux
MS Internet Explorer
Netscape 4.7/6.1
Mozilla v1.0
Opera
Win-CE and pen-based devices

13. Local Data Mirrors MySQL DataMart(s) SDSC SOAP Server
Mirror Manager
MySQL DataMart(s)
Structure assignment by PSI-BLAST
Structure assignment by 123D
Domain location prediction
SDSC
SOAP Server
Request for bulk data streams
Data Management Layer
MySQL DataMart(s)
Structure assignment by PSI-BLAST
Structure assignment by 123D
Domain location prediction
BLAST server
SOAP Server
Web Interface

14. Local Data Mirrors Support for server platforms, i.e. Sparc Solaris
IRIX
Linux
Based on MySQL + Apache because of availability
Automated mirror registration and listing
User-friendly admin for mirror maintenance
Means of metering of data usage per species data stream to generate revenue from industry

15. EOL Notebook EOL DataMart SOAP Server EOL SOAP Queries XML/RDF store
Structure assignment by PSI-BLAST
Structure assignment by 123D
Domain location prediction
SOAP Server
Encyclopedia of Life
EOL SOAP Queries
Invoke
Virtual community messaging
XML/RDF store
Metadata sharing
BLAST Data
Keyword data
Scheduler
Stored queries
BLAST
Annotations
Keyword queries
Session info

16. EOL Notebook
Provides a consistent, advanced, cross-platform GUI to view returned data from queries to the EOL database via Web Services.
Provide persistence of both queries and returned data via local XML database
Provide mechanism to enable unattended, scheduled, periodic queries
Provides means to annotate data and results and share those with others, in effect a scientific Napster
Provide means to create virtual community(s)

17. Summary
1. EOL is a large-scale data analysis project, one of the largest biological computations attempted, whose results will be eagerly awaited by an enormous number of biologists
2. Core scientific analysis techniques well-proven in existing arabidopsis project
3. It’s a perfect choice as a charter application for the TeraGrid
Very large scale computation
Pipeline-type computations well suited to the Grid platform
High visibility and very practical use of TeraGrid results
TeraGrid name will become associated with high quality data analysis