loading...
 This Article 
   
 Share 
   
 Bibliographic References 
   
 Add to: 
 
Digg
Furl
Spurl
Blink
Simpy
Google
Del.icio.us
Y!MyWeb
 
 Search 
   
18th International Parallel and Distributed Processing Symposium (IPDPS'04) - Workshop 9
Constrained De Novo Peptide Identification via Multi-Objective Optimization
Santa Fe, New Mexico
April 26-April 30
ISBN: 0-7695-2132-0
ASCII Text
x 
 
J. M. Malard, A. Heredia-Langner, D. J. Baxter, K. H. Jarman, W. R. Cannon, "Constrained De Novo Peptide Identification via Multi-Objective Optimization," Parallel and Distributed Processing Symposium, International, vol. 10, pp. 191a, 18th International Parallel and Distributed Processing Symposium (IPDPS'04) - Workshop 9, 2004.
 
 
BibTex
x
 
@article{ 10.1109/IPDPS.2004.1303208,
author = {J. M. Malard and A. Heredia-Langner and D. J. Baxter and K. H. Jarman and W. R. Cannon},
title = {Constrained De Novo Peptide Identification via Multi-Objective Optimization},
journal ={Parallel and Distributed Processing Symposium, International},
volume = {10},
year = {2004},
isbn = {0-7695-2132-0},
pages = {191a},
doi = {http://doi.ieeecomputersociety.org/10.1109/IPDPS.2004.1303208},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
x 
 
TY - CONF
JO - Parallel and Distributed Processing Symposium, International
TI - Constrained De Novo Peptide Identification via Multi-Objective Optimization
SN - 0-7695-2132-0
SP
EP
A1 - J. M. Malard,
A1 - A. Heredia-Langner,
A1 - D. J. Baxter,
A1 - K. H. Jarman,
A1 - W. R. Cannon,
PY - 2004
KW - null
VL - 10
JA - Parallel and Distributed Processing Symposium, International
ER -
 
J. M. Malard, Pacific Northwest National Laboratory
A. Heredia-Langner, Pacific Northwest National Laboratory
D. J. Baxter, Pacific Northwest National Laboratory
K. H. Jarman, Pacific Northwest National Laboratory
W. R. Cannon, Pacific Northwest National Laboratory
Automatic de novo peptide identification from collision-induced dissociation tandem mass spectrometry data is made difficult by large plateaus in the fitness landscapes of scoring functions and the fuzzy nature of the constraints that is due to noise in the data. Two different scoring functions are combined into a parallel multi-objective optimization framework.
Citation:
J. M. Malard, A. Heredia-Langner, D. J. Baxter, K. H. Jarman, W. R. Cannon, "Constrained De Novo Peptide Identification via Multi-Objective Optimization," ipdps, vol. 10, pp.191a, 18th International Parallel and Distributed Processing Symposium (IPDPS'04) - Workshop 9, 2004
Usage of this product signifies your acceptance of the Terms of Use.