Journal Article

A performance enhanced PSI-BLAST based on hybrid alignment

Yuheng Li, Nicholas Chia, Mario Lauria and Ralf Bundschuh

in Bioinformatics

Volume 27, issue 1, pages 31-37
Published in print January 2011 | ISSN: 1367-4803
Published online November 2010 | e-ISSN: 1460-2059 | DOI:
A performance enhanced PSI-BLAST based on hybrid alignment

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Motivation: Sequence alignment is one of the most popular tools of modern biology. NCBI's PSI-BLAST utilizes iterative model building in order to better detect distant homologs with greater sensitivity than non-iterative BLAST. However, PSI-BLAST's performance is limited by the fact that it relies on deterministic alignments. Using a semi-probabilistic alignment scheme such as Hybrid alignment should allow for better informed model building and improved identification of homologous sequences, particularly remote homologs.

Results: We have built a new version of the tool in which the Smith-Waterman alignment algorithm core is replaced by the hybrid alignment algorithm. The favorable statistical properties of the hybrid algorithm allow the introduction of position-specific gap penalties in Hybrid PSI-BLAST. This improves the position-specific modeling of protein families and results in an overall improvement of performance.

Availability: Source code is freely available for download at, implemented in C and supported on linux.


Supplementary information:Supplementary data are available at Bioinformatics online.

Journal Article.  5958 words.  Illustrated.

Subjects: Bioinformatics and Computational Biology

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