High-performance peptide identification by tandem mass spectrometry allows reliable automatic data processing in proteomics.
Proteomics
; 4(7): 1977-84, 2004 Jul.
Article
em En
| MEDLINE
| ID: mdl-15221758
ABSTRACT
In a previous paper we introduced a novel model-based approach (OLAV) to the problem of identifying peptides via tandem mass spectrometry, for which early implementations showed promising performance. We recently further improved this performance to a remarkable level (1-2% false positive rate at 95% true positive rate) and characterized key properties of OLAV like robustness and training set size. We present these results in a synthetic and coherent way along with detailed performance comparisons, a new scoring component making use of peptide amino acidic composition, and new developments like automatic parameter learning. Finally, we discuss the impact of OLAV on the automation of proteomics projects.
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Coleções:
01-internacional
Base de dados:
MEDLINE
Assunto principal:
Peptídeos
/
Proteômica
Tipo de estudo:
Diagnostic_studies
/
Prognostic_studies
Limite:
Humans
Idioma:
En
Ano de publicação:
2004
Tipo de documento:
Article