Statements in which the resource exists as a subject.
PredicateObject
rdf:type
lifeskim:mentions
pubmed:issue
18
pubmed:dateCreated
2006-9-18
pubmed:abstractText
The newly available techniques for sensitive proteome analysis and the resulting amount of data require a new bioinformatics focus on automatic methods for spectrum reprocessing and peptide/protein validation. Manual validation of results in such studies is not feasible and objective enough for quality relevant interpretation. The necessity for tools enabling an automatic quality control is, therefore, important to produce reliable and comparable data in such big consortia as the Human Proteome Organization Brain Proteome Project. Standards and well-defined processing pipelines are important for these consortia. We show a way for choosing the right database model, through collecting data, processing these with a decoy database and end up with a quality controlled protein list merged from several search engines, including a known false-positive rate.
pubmed:language
eng
pubmed:journal
pubmed:citationSubset
IM
pubmed:chemical
pubmed:status
MEDLINE
pubmed:month
Sep
pubmed:issn
1615-9853
pubmed:author
pubmed:issnType
Print
pubmed:volume
6
pubmed:owner
NLM
pubmed:authorsComplete
Y
pubmed:pagination
5015-29
pubmed:dateRevised
2007-11-15
pubmed:meshHeading
pubmed:year
2006
pubmed:articleTitle
Automated reprocessing pipeline for searching heterogeneous mass spectrometric data of the HUPO Brain Proteome Project pilot phase.
pubmed:affiliation
Medizinisches Proteom-Center, Ruhr-Universität Bochum, Bochum, Germany. Christian.Stephan@rub.de
pubmed:publicationType
Journal Article, Research Support, Non-U.S. Gov't