DocumentCode
2463021
Title
Protein Sequencing with an Adaptive Genetic Algorithm from Tandem Mass Spectrometry
Author
Boisson, Jean-Charles ; Jourdan, Laetitia ; Talbi, El-Ghazali ; Rolando, Christian
Author_Institution
LIFL/INRIA Futurs., Villeneuve d´´Ascq
fYear
0
fDate
0-0 0
Firstpage
1412
Lastpage
1419
Abstract
In Proteomics, only the de novo peptide sequencing approach allows a partial amino acid sequence of a peptide to be found from a MS/MS spectrum. In this article a preliminary work is presented to discover a complete protein sequence from spectral data (MS and MS/MS spectra). For the moment, our approach only uses MS spectra. A genetic algorithm (GA) has been designed with a new evaluation function which works directly with a complete MS spectrum as input and not with a mass list like the other methods using this kind of data. Thus the mono isotopic peak extraction step which needs a human intervention is deleted. The goal of this approach is to discover the sequence of unknown proteins and to allow a better understanding of the differences between experimental proteins and proteins from databases.
Keywords
genetic algorithms; mass spectra; proteins; adaptive genetic algorithm; amino acid; de novo peptide sequencing; protein sequencing; proteomics; tandem mass spectrometry; Algorithm design and analysis; Amino acids; Data mining; Genetic algorithms; Humans; MONOS devices; Mass spectroscopy; Peptides; Protein sequence; Proteomics;
fLanguage
English
Publisher
ieee
Conference_Titel
Evolutionary Computation, 2006. CEC 2006. IEEE Congress on
Conference_Location
Vancouver, BC
Print_ISBN
0-7803-9487-9
Type
conf
DOI
10.1109/CEC.2006.1688474
Filename
1688474
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