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Nucleic Acids Research 2005 33(Web Server Issue):W376-W381; doi:10.1093/nar/gki461
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© The Author 2005. Published by Oxford University Press. All rights reserved
The online version of this article has been published under an open access model. Users are entitled to use, reproduce, disseminate, or display the open access version of this article for non-commercial purposes provided that: the original authorship is properly and fully attributed; the Journal and Oxford University Press are attributed as the original place of publication with the correct citation details given; if an article is subsequently reproduced or disseminated not in its entirety but only in part or as a derivative work this must be clearly indicated. For commercial re-use, please contact journals.permissions{at}oupjournals.org

Article

DeNovoID: a web-based tool for identifying peptides from sequence and mass tags deduced from de novo peptide sequencing by mass spectroscopy

Brian D. Halligan*, Victor Ruotti, Simon N. Twigger and Andrew S. Greene1

Bioinformatics Research Center, Medical College of Wisconsin 8701 Watertown Plank Road, Milwaukee, WI 53213, USA 1Biotechnology and Biomedical Engineering Center, Medical College of Wisconsin 8701 Watertown Plank Road, Milwaukee, WI 53213, USA

*To whom correspondence should be addressed. Tel: +1 414 456 8838; Fax: +1 414 456 6595; Email: Halligan{at}mcw.edu

Received February 14, 2005. Revised April 4, 2005. Accepted April 13, 2005.

One of the core activities of high-throughput proteomics is the identification of peptides from mass spectra. Some peptides can be identified using spectral matching programs like Sequest or Mascot, but many spectra do not produce high quality database matches. De novo peptide sequencing is an approach to determine partial peptide sequences for some of the unidentified spectra. A drawback of de novo peptide sequencing is that it produces a series of ordered and disordered sequence tags and mass tags rather than a complete, non-degenerate peptide amino acid sequence. This incomplete data is difficult to use in conventional search programs such as BLAST or FASTA. DeNovoID is a program that has been specifically designed to use degenerate amino acid sequence and mass data derived from MS experiments to search a peptide database. Since the algorithm employed depends on the amino acid composition of the peptide and not its sequence, DeNovoID does not have to consider all possible sequences, but rather a smaller number of compositions consistent with a spectrum. DeNovoID also uses a geometric indexing scheme that reduces the number of calculations required to determine the best peptide match in the database. DeNovoID is available at http://proteomics.mcw.edu/denovoid.


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