By Topic

Solving the Problem of Trans-Genomic Query with Alignment Tables

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

5 Author(s)
Parker, D.S. ; Dept. of Comput. Sci., Univ. of California at Los Angeles, Los Angeles, CA ; Ruey-Lung Hsiao ; Yi Xing ; Resch, A.M.
more authors

The trans-genomic query (TGQ) problem-enabling the free query of biological information, even across genomes-is a central challenge facing bioinformatics. Solutions to this problem can alter the nature of the field, moving it beyond the jungle of data integration and expanding the number and scope of questions that can be answered. An alignment table is a binary relationship on locations (sequence segments). An important special case of alignment tables are hit tables-tables of pairs of highly similar segments produced by alignment tools like BLAST. However, alignment tables also include general binary relationships and can represent any useful connection between sequence locations. They can be curated and provide a high-quality queryable backbone of connections between biological information. Alignment tables thus can be a natural foundation for TGQ, as they permit a central part of the TGQ problem to be reduced to purely technical problems involving tables of locations. Key challenges in implementing alignment tables include efficient representation and indexing of sequence locations. We define a location data type that can be incorporated naturally into common off-the-shelf database systems. We also describe an implementation of alignment tables in BLASTGRES, an extension of the open-source POSTGRESQL database system that provides indexing and operators on locations required for querying alignment tables. This paper also reviews several successful large-scale applications of alignment tables for TGQ. Tables with millions of alignments have been used in queries about alternative splicing, an area of genomic analysis concerning the way in which a single gene can yield multiple transcripts. Comparative genomics is a large potential application area for TGQ and alignment tables.

Published in:

Computational Biology and Bioinformatics, IEEE/ACM Transactions on  (Volume:5 ,  Issue: 3 )