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Solving the problem of Trans-Genomic Query with alignment tables.

Douglass Stott Parker¹, Ruey-Lung Hsiao, Yi Xing

¹Computer Science Department, University of California at Los Angeles, 3532 Boelter Hall, Los Angeles, CA 90095, USA. stott@cs.ucla.edu

IEEE/ACM Transactions on Computational Biology and Bioinformatics

|August 2, 2008

Summary

Trans-genomic query (TGQ) enables biological information retrieval across genomes. Alignment tables provide a scalable solution for TGQ by efficiently indexing sequence locations in databases like BLASTGRES.

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Area of Science:

Bioinformatics
Genomics
Computational Biology

Background:

The trans-genomic query (TGQ) problem presents a significant challenge in bioinformatics, hindering seamless biological information retrieval across different genomes.
Existing data integration methods are complex, limiting the scope of biological questions that can be addressed.

Purpose of the Study:

To introduce alignment tables as a foundational element for solving the TGQ problem.
To present efficient methods for representing and indexing sequence locations within databases.
To demonstrate the utility of alignment tables through large-scale applications.

Main Methods:

Defining a location datatype compatible with standard database systems.
Implementing alignment tables in BLASTGRES, a PostgreSQL extension, with specialized indexing and operators.
Reviewing large-scale applications of alignment tables for TGQ.

Main Results:

Alignment tables offer a high-quality, queryable backbone for biological information, reducing TGQ to technical table-based problems.
The BLASTGRES implementation efficiently handles millions of alignments.
Successful applications include queries related to alternative splicing and comparative genomics.

Conclusions:

Alignment tables are a viable and scalable solution for the trans-genomic query problem.
Efficient data representation and database indexing are crucial for enabling complex biological queries.
Alignment tables have broad applicability in genomic analysis and comparative genomics.