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Bioinformatics Advance Access originally published online on May 6, 2005
Bioinformatics 2005 21(14):3189-3190; doi:10.1093/bioinformatics/bti488
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© The Author 2005. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions{at}oupjournals.org

Fast parsers for Entrez Gene

Mingyi Liu and Andrei Grigoriev *

GPC Biotech AG Fraunhoferstrasse 20, 82152 Martinsried, Germany

*To whom correspondence should be addressed.

Summary:NCBI completed the transition of its main genome annotation database from Locuslink to Entrez Gene in Spring 2005. However, to this date few parsers exist for the Entrez Gene annotation file. Owing to the widespread use of Locuslink and the popularity of Perl programming language in bioinformatics, a publicly available high performance Entrez Gene parser in Perl is urgently needed. We present four such parsers that were developed using several parsing approaches (Parse::RecDescent, Parse::Yapp, Perl-byacc and Perl 5 regular expressions) and provide the first in-depth comparison of these sophisticated Perl tools. Our fastest parser processes the entire human Entrez Gene annotation file in under 12 min on one Intel Xeon 2.4 GHz CPU and can be of help to the bioinformatics community during and after the transition from Locuslink to Entrez Gene.

Availability:Source codes are available under the Perl and GNU public license at http://sourceforge.net/projects/egparser/

Contact:andrei.grigoriev{at}gpc-biotech.com

Received on March 14, 2005; revised on May 3, 2005; accepted on May 3, 2005

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[Abstract] [Full Text] [PDF]


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