Randomized Sequence Databases for Tandem Mass Spectrometry Peptide and Protein Identification

2005 ◽  
Vol 9 (4) ◽  
pp. 364-379 ◽  
Author(s):  
Roger Higdon ◽  
Jason M. Hogan ◽  
Gerald Van Belle ◽  
Eugene Kolker
Keyword(s):  
Mass Spectrometry ◽  
Tandem Mass Spectrometry ◽  
Protein Identification ◽  
Tandem Mass ◽  
Sequence Databases

Data Requirements for Protein Identification Using Chemically-Assisted Fragmentation and Tandem Mass Spectrometry

2005 ◽  
Vol 11 (2) ◽  
pp. 161-167 ◽  
Author(s):  
Kenton D. Juhlin ◽  
Dionne D. Swift ◽  
Martin P. Lacey ◽  
Paul E. Correa ◽  
Thomas W. Keough
Keyword(s):  
Mass Spectrometry ◽  
Tandem Mass Spectrometry ◽  
Protein Sequence ◽  
Protein Identification ◽  
Sequence Data ◽  
Mass Spectrometry Data ◽  
Peptide Sequence ◽  
Tandem Mass ◽  
Sequence Databases ◽  
Data Requirements

Many laboratories identify proteins by searching tandem mass spectrometry data against genomic or protein sequence databases. These database searches typically use the measured peptide masses or the derived peptide sequence and, in this paper, we focus on the latter. We study the minimum peptide sequence data requirements for definitive protein identification from protein sequence databases. Accurate mass measurements are not needed for definitive protein identification, even when a limited amount of sequence data is available for searching. This information has implications for the mass spectrometry performance (and cost), data base search strategies and proteomics research.

Data Mining in Protein Identification by Tandem Mass Spectrometry

2011 ◽  
pp. 472-478
Author(s):  
Haipeng Wang
Keyword(s):  
Mass Spectrometry ◽  
Data Mining ◽  
Tandem Mass Spectrometry ◽  
Large Scale ◽  
Protein Identification ◽  
Peptide Fragmentation ◽  
Tandem Mass ◽  
Fragmentation Pattern ◽  
Post Translational Modification ◽  
Challenges And Opportunities

Protein identification (sequencing) by tandem mass spectrometry is a fundamental technique for proteomics which studies structures and functions of proteins in large scale and acts as a complement to genomics. Analysis and interpretation of vast amounts of spectral data generated in proteomics experiments present unprecedented challenges and opportunities for data mining in areas such as data preprocessing, peptide-spectrum matching, results validation, peptide fragmentation pattern discovery and modeling, and post-translational modification (PTM) analysis. This article introduces the basic concepts and terms of protein identification and briefly reviews the state-of-the-art relevant data mining applications. It also outlines challenges and future potential hot spots in this field.

scholarly journals EBP, a Program for Protein Identification Using Multiple Tandem Mass Spectrometry Datasets

2006 ◽  
Vol 6 (3) ◽  
pp. 527-536 ◽  
Author(s):  
Thomas S. Price ◽  
Margaret B. Lucitt ◽  
Weichen Wu ◽  
David J. Austin ◽  
Angel Pizarro ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Tandem Mass Spectrometry ◽  
Protein Identification ◽  
Tandem Mass
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