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Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/2818

Title: Bioinformatic analysis of peptide precursor proteins
Authors: Baggerman, G.
Liu, Feng
Wets, Geert
Schoofs, L.
Issue Date: 2005
Publisher: NEW YORK ACAD SCIENCES
Citation: ANNALS OF THE NEW YORK ACADEMY OF SCIENCES, 1040. p. 59-65
Abstract: Neuropeptides are among the most important signal molecules in animals. Traditional identification of peptide hormones through peptide purification is a tedious and time-consuming process. With the advent of the genome sequencing projects, putative peptide precursor can be mined from the genome. However, because bioactive peptides are usually quite short in length and because the active core of a peptide is often limited to only a few amino acids, using the BLAST search engine to identify neuropeptide precursors in the genome is difficult and sometimes impossible. To overcome these shortcomings, we subject the entire set of all known Drosophila melanogaster peptide precursor sequences to motif-finding algorithms in search of a motif that is common for all prepropeptides and that could be used in the search for new peptide precursors.
Notes: Catholic Univ Louvain, Lab Dev Physiol Genom & Proteom, B-3000 Louvain, Belgium. Univ Limburg, Fac Appl Econ, Data Anal & Modeling Grp, B-3590 Diepenbeek, Belgium.Baggerman, G, Catholic Univ Louvain, Lab Dev Physiol Genom & Proteom, Naamsestr 59, B-3000 Louvain, Belgium.geert.baggerman@bio.kuleuven.ac.be
URI: http://hdl.handle.net/1942/2818
DOI: 10.1196/annals.1327.006
ISI #: 000230936100006
Category: A1
Type: Journal Contribution
Validation: ecoom, 2006
Appears in Collections: Research publications

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