Interoperation of Molecular Biology Databases

1
Interoperation of Molecular Biology Databases

• Peter D. Karp, Ph.D.
• Bioinformatics Research Group
• SRI International
• Menlo Park, CA
• pkarp_at_ai.sri.com

2
Main Message

• Interoperation of molecular-biology databases is
  a challenging problem of critical importance
• DOE should initiate a program in interoperation
  of molecular biology databases
• Pursue both warehouse approach and multidatabase
  approach
• Major progress possible within 5 years

3
Motivations

• Important biological problems require access to
  multiple bioinformatics databases
• Different problems require different sets of
  databases
• Hundreds of bioinformatics databases exist
• Nucleic Acids Research 322004 Database issue
• Nucleic Acids Research DB list
  http//www3.oup.co.uk/nar/database/a/
• 350 databases listed in 2002
• 560 databases listed in 2004
• Applications of integration include
• Complex queries
• Comparison of overlapping sources
• Data mining

4
Bioinformatics Databases

• Tremendous progress in point-and-click access for
  biologist users
• Less progress toward providing a computable,
  interoperable infrastructure for large-scale data
  mining
• Every large-scale mining/learning problem
  requires time consuming crafting of
  input/training datasets

5
Warehouse Approach vsMultidatabase Approach

• Multidatabase query approaches assume databases
  are in a queryable DBMS
• Most sites that do operate DBMSs do not allow
  remote query access because of security and
  loading concerns
• Users want to control data stability
• Users want to control hardware applied to problem
• Internet bandwidth limits query throughput
• Users need to capture, integrate and publish
  locally produced data of different types
• Replicating and refreshing very large sources is
  expensive
• Multidatabase and Warehouse approaches
  complementary

6
SRI BioWarehouseProject Goal

• Create a toolkit for constructing bioinformatics
  database warehouses that integrate sets of
  bioinformatics databases into one physical DBMS

7
BioWarehouse Approach

• Warehouse schema defines many bioinformatics
  datatypes
• Create loaders for public bioinformatics DBs
• Parse file format for the DB
• Apply semantic transformations
• Insert database into warehouse tables
• Oracle and MySQL implementations
• Warehouse query access mechanisms
• SQL queries via JDBC,Lisp,Perl, ODBC, OAA

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Warehouse Schema

• Manages many bioinformatics datatypes
  simultaneously
• Pathways, Reactions, Chemicals
• Proteins, Genes, Replicons
• Sequences, Sequence Features
• Organisms, Taxonomic relationships
• Computations (sequence matches)
• Citations, Controlled vocabularies
• Links to external databases
• Each type of warehouse object implemented through
  one or more relational tables (currently 43)

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Warehouse Schema

• Manages multiple datasets simultaneously
• Dataset Single version of a database
• Allows version comparison
• Multiple software tools or experiments require
  access to different versions
• Each dataset is a warehouse entity
• Every warehouse object is registered in a dataset
• Different databases storing the same biological
  datatypes are coerced into same warehouse tables
• Design of most datatypes inspired by multiple
  databases
• Representational tricks to decrease schema bloat
• Single space of primary keys
• Single set of satellite tables such as for
  synonyms, citations, comments, etc.

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Current Databases Supported by BioWarehouse

• BioCyc
• 15 genomes and metabolic networks
• Swiss-Prot, TrEMBL
• 1.3M proteins
• ENZYME
• KEGG
• NCBI Taxonomy
• CMR
• 105 genomes, 250K genes, 250K proteins
• Applications
• DARPA BioSpice program on biological simulation
• Study of sequence coverage of known enzymes

11
Summary

• Interoperation of molecular-biology databases is
  a challenging problem of critical importance
• DOE should initiate a program in interoperation
  of molecular biology databases
• Pursue both warehouse approach and multidatabase
  approach
• Major progress possible within 5 years