Intensity-based protein identification by machine learning from a library of tandem mass spectra

2004 ◽  
Vol 22 (2) ◽  
pp. 214-219 ◽  
Author(s):  
Joshua E Elias ◽  
Francis D Gibbons ◽  
Oliver D King ◽  
Frederick P Roth ◽  
Steven P Gygi
Keyword(s):  
Machine Learning ◽  
Mass Spectra ◽  
Protein Identification ◽  
Tandem Mass ◽  
Tandem Mass Spectra

scholarly journals Features-Based Deisotoping Method for Tandem Mass Spectra

2011 ◽  
Vol 2011 ◽  
pp. 1-12 ◽  
Author(s):  
Zheng Yuan ◽  
Jinhong Shi ◽  
Wenjun Lin ◽  
Bolin Chen ◽  
Fang-Xiang Wu
Keyword(s):  
Mass Spectra ◽  
Protein Identification ◽  
Score Function ◽  
Tandem Mass ◽  
Isotopic Cluster ◽  
Tandem Mass Spectra ◽  
Fragment Ions ◽  
The Relationship ◽  
Cluster Graphs

For high-resolution tandem mass spectra, the determination of monoisotopic masses of fragment ions plays a key role in the subsequent peptide and protein identification. In this paper, we present a new algorithm for deisotoping the bottom-up spectra. Isotopic-cluster graphs are constructed to describe the relationship between all possible isotopic clusters. Based on the relationship in isotopic-cluster graphs, each possible isotopic cluster is assessed with a score function, which is built by combining nonintensity and intensity features of fragment ions. The non-intensity features are used to prevent fragment ions with low intensity from being removed. Dynamic programming is adopted to find the highest score path with the most reliable isotopic clusters. The experimental results have shown that the average Mascot scores and F-scores of identified peptides from spectra processed by our deisotoping method are greater than those by YADA and MS-Deconv software.

scholarly journals An unsupervised machine learning method for assessing quality of tandem mass spectra

2012 ◽  
Vol 10 (Suppl 1) ◽  
pp. S12 ◽  
Author(s):  
Wenjun Lin ◽  
Jianxin Wang ◽  
Wen-Jun Zhang ◽  
Fang-Xiang Wu
Keyword(s):  
Machine Learning ◽  
Mass Spectra ◽  
Tandem Mass ◽  
Machine Learning Method ◽  
Learning Method ◽  
Unsupervised Machine Learning ◽  
Tandem Mass Spectra

Current Status of Computational Approaches for Protein Identification Using Tandem Mass Spectra

2007 ◽  
Vol 4 (3) ◽  
pp. 121-130 ◽  
Author(s):  
Xiang Zhang ◽  
Cheolhwan Oh ◽  
Catherine Riley ◽  
Charles Buck
Keyword(s):  
Mass Spectra ◽  
Protein Identification ◽  
Current Status ◽  
Tandem Mass ◽  
Computational Approaches ◽  
Tandem Mass Spectra

scholarly journals Separating the Wheat from the Chaff: Unbiased Filtering of Background Tandem Mass Spectra Improves Protein Identification

2008 ◽  
Vol 7 (8) ◽  
pp. 3382-3395 ◽  
Author(s):  
Magno Junqueira ◽  
Victor Spirin ◽  
Tiago Santana Balbuena ◽  
Patrice Waridel ◽  
Vineeth Surendranath ◽  
...  
Keyword(s):  
Mass Spectra ◽  
Protein Identification ◽  
Tandem Mass ◽  
Tandem Mass Spectra
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