Journal Article

PESTAS: a web server for EST analysis and sequence mining

Seong-Hyeuk Nam, Dae-Won Kim, Tae-Sung Jung, Young-Sang Choi, Dong-Wook Kim, Han-Suk Choi, Sang-Haeng Choi and Hong-Seog Park

in Bioinformatics

Volume 25, issue 14, pages 1846-1848
Published in print July 2009 | ISSN: 1367-4803
Published online May 2009 | e-ISSN: 1460-2059 | DOI:
PESTAS: a web server for EST analysis and sequence mining

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Summary: We have developed a web server for the high-throughput annotation of expressed sequence tags (ESTs) called pipeline for EST analysis service (PESTAS). PESTAS processes entire datasets with an automated pipeline of 13 analytic services, then deposits the data into the MySQL database and transforms it into three kinds of reports: preprocessing, assembling and annotation. All annotated information is provided to the scientist and can be downloaded through a web browser. To get more relevant functional annotation results, a curation function was introduced with which biologists can easily change the best-hit annotation information. We included a gene chip module that detects gene expression differences between libraries by comparing accession number counts from BLAST search results. PESTAS also provides access to the pathway information of KEGG, which is useful for mapping the relationships among networks of annotated enzymes, and is especially valuable for those researchers interested in biological pathways.

Availability: PESTAS is available at

Supplementary information: Supplementary data are available at


Journal Article.  1197 words.  Illustrated.

Subjects: Bioinformatics and Computational Biology

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