Document Detail


Modeling mass spectrometry-based protein analysis.
MedLine Citation:
PMID:  21082431     Owner:  NLM     Status:  MEDLINE    
Abstract/OtherAbstract:
The success of mass spectrometry based proteomics depends on efficient methods for data analysis. These methods require a detailed understanding of the information value of the data. Here, we describe how the information value can be elucidated by performing simulations using synthetic data.
Authors:
Jan Eriksson; David Fenyö
Publication Detail:
Type:  Journal Article; Research Support, N.I.H., Extramural; Research Support, Non-U.S. Gov't    
Journal Detail:
Title:  Methods in molecular biology (Clifton, N.J.)     Volume:  694     ISSN:  1940-6029     ISO Abbreviation:  Methods Mol. Biol.     Publication Date:  2011  
Date Detail:
Created Date:  2010-11-18     Completed Date:  2011-02-23     Revised Date:  2013-09-03    
Medline Journal Info:
Nlm Unique ID:  9214969     Medline TA:  Methods Mol Biol     Country:  United States    
Other Details:
Languages:  eng     Pagination:  109-17     Citation Subset:  IM    
Affiliation:
Swedish University of Agricultural Sciences, Uppsala, Sweden.
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MeSH Terms
Descriptor/Qualifier:
Computer Simulation*
Mass Spectrometry / methods*
Molecular Weight
Peptide Mapping
Peptides / analysis,  chemistry
Proteins / analysis*,  chemistry
Tandem Mass Spectrometry
Grant Support
ID/Acronym/Agency:
CA126485/CA/NCI NIH HHS; DE018385/DE/NIDCR NIH HHS; NS050276/NS/NINDS NIH HHS; P41 RR000862/RR/NCRR NIH HHS; RR00862/RR/NCRR NIH HHS; RR022220/RR/NCRR NIH HHS; U54 RR022220/RR/NCRR NIH HHS
Chemical
Reg. No./Substance:
0/Peptides; 0/Proteins
Comments/Corrections

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine


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