Linked Life Data

14632076

Source:http://linkedlifedata.com/resource/pubmed/id/14632076

Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
17
pubmed:dateCreated
2003-11-24
pubmed:abstractText
A statistical model is presented for computing probabilities that proteins are present in a sample on the basis of peptides assigned to tandem mass (MS/MS) spectra acquired from a proteolytic digest of the sample. Peptides that correspond to more than a single protein in the sequence database are apportioned among all corresponding proteins, and a minimal protein list sufficient to account for the observed peptide assignments is derived using the expectation-maximization algorithm. Using peptide assignments to spectra generated from a sample of 18 purified proteins, as well as complex H. influenzae and Halobacterium samples, the model is shown to produce probabilities that are accurate and have high power to discriminate correct from incorrect protein identifications. This method allows filtering of large-scale proteomics data sets with predictable sensitivity and false positive identification error rates. Fast, consistent, and transparent, it provides a standard for publishing large-scale protein identification data sets in the literature and for comparing the results obtained from different experiments.
pubmed:grant
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:chemical
pubmed:status
MEDLINE
pubmed:month
Sep
pubmed:issn
0003-2700
pubmed:author
pubmed:issnType
Print
pubmed:day
1
pubmed:volume
75
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
4646-58
pubmed:dateRevised
2007-11-14
pubmed:meshHeading
pubmed:year
2003
pubmed:articleTitle
A statistical model for identifying proteins by tandem mass spectrometry.
pubmed:affiliation
Institute for Systems Biology, 1441 North 34th Street, Seattle, Washington 98103, USA. nesvi@systemsbiology.org
pubmed:publicationType
Journal Article, Research Support, U.S. Gov't, P.H.S., Research Support, U.S. Gov't, Non-P.H.S., Research Support, Non-U.S. Gov't