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
Link To Document :
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