Methods, algorithms and tools in computational proteomics: A practical point of view

被引:57
作者
Matthiesen, Rune [1 ]
机构
[1] CIBER HEPAD, CIC BioGUNE, Bioinformat Grp, Derio 48160, Spain
关键词
bioinformatics; database search; quantitative proteomics;
D O I
10.1002/pmic.200700116
中图分类号
Q5 [生物化学];
学科分类号
071010 ; 081704 ;
摘要
Computational MS-based proteomics is an emerging field arising from the demand of high throughput analysis in numerous large-scale experimental proteomics projects. The review provides a broad overview of a number of computational tools available for data analysis of MS-based proteomics data and gives appropriate literature references to detailed description of algorithms. The review provides, to some extent, discussion of algorithms and methods for peptide and protein identification using MS data, quantitative proteomics, and data storage. The hope is that it will stimulate discussion and further development in computational proteomics. Computational proteomics deserves more scientific attention. There are far fewer computational tools and methods available for proteomics compared to the number of microarray tools, despite the fact that data analysis in proteomics is much more complex than microarray analysis.
引用
收藏
页码:2815 / 2832
页数:18
相关论文
共 157 条
[1]  
ALORIA K, 2007, PROTEOMICS PATHOLOGY
[2]   A new algorithm for the evaluation of shotgun peptide sequencing in proteomics: Support vector machine classification of peptide MS/MS spectra and SEQUEST scores [J].
Anderson, DC ;
Li, WQ ;
Payan, DG ;
Noble, WS .
JOURNAL OF PROTEOME RESEARCH, 2003, 2 (02) :137-146
[3]   Proteome and proteomics: New technologies, new concepts, and new words [J].
Anderson, NL ;
Anderson, NG .
ELECTROPHORESIS, 1998, 19 (11) :1853-1861
[4]  
[Anonymous], 2001, Bioinformatics
[5]   AUTOMATIC CLASSIFICATION OF TWO-DIMENSIONAL GEL-ELECTROPHORESIS PICTURES BY HEURISTIC CLUSTERING ANALYSIS - A STEP TOWARD MACHINE LEARNING [J].
APPEL, R ;
HOCHSTRASSER, D ;
ROCH, C ;
FUNK, M ;
MULLER, AF ;
PELLEGRINI, C .
ELECTROPHORESIS, 1988, 9 (03) :136-142
[6]   THE MELANIE PROJECT - FROM A BIOPSY TO AUTOMATIC PROTEIN MAP INTERPRETATION BY COMPUTER [J].
APPEL, RD ;
HOCHSTRASSER, DF ;
FUNK, M ;
VARGAS, JR ;
PELLEGRINI, C ;
MULLER, AF ;
SCHERRER, JR .
ELECTROPHORESIS, 1991, 12 (10) :722-735
[7]   Melanie II - a third-generation software package for analysis of two-dimensional electrophoresis images: I. Features and user interface [J].
Appel, RD ;
Palagi, PM ;
Walther, D ;
Vargas, JR ;
Sanchez, JC ;
Ravier, F ;
Pasquali, C ;
Hochstrasser, DF .
ELECTROPHORESIS, 1997, 18 (15) :2724-2734
[8]   Protein sequence databases [J].
Apweiler, R ;
Bairoch, A ;
Wu, CH .
CURRENT OPINION IN CHEMICAL BIOLOGY, 2004, 8 (01) :76-80
[9]   A probability-based approach for high-throughput protein phosphorylation analysis and site localization [J].
Beausoleil, Sean A. ;
Villen, Judit ;
Gerber, Scott A. ;
Rush, John ;
Gygi, Steven P. .
NATURE BIOTECHNOLOGY, 2006, 24 (10) :1285-1292
[10]   Quantitative proteomic analysis of posttranslational modifications of human histones [J].
Beck, Hans Christian ;
Nielsen, Eva C. ;
Matthiesen, Rune ;
Jensen, Lars H. ;
Sehested, Maxwell ;
Finn, Paul ;
Grauslund, Morten ;
Hansen, Anne Maria ;
Jensen, Ole Norregaard .
MOLECULAR & CELLULAR PROTEOMICS, 2006, 5 (07) :1314-1325