The full text of this article:

Proteomic data mining using predicted peptide chromatographic retention times
by Brian Tripet, Megha Renuka Jayadev, Don Blow, Cao Nguyen, Robert S. Hodges, Krzysztof J. Cios
International Journal of Bioinformatics Research and Applications (IJBRA), Vol. 3, No. 4, 2007
Abstract: Correct identification of proteins from peptide fragments is important for proteomic analyses. Peptides are initially separated by Reversed-Phase High-Performance Liquid Chromatography (RP-HPLC) before Mass Spectrometry (MS) identification. At the present time, peptide fragment retention (separation) time is not used as a useful scoring filter for identification of the peptide fragments and their parent proteins. In the present paper, we present a new web-based tool for the prediction of peptide fragment retention times and its use in compiling a database of ∼133,000 peptide fragments computationally obtained by digestion with trypsin of 4,265 E. coli – K12 proteins. The retention calculation is based on the described formulae and the fragments/protein identification was carried out using a simple search-scoring algorithm.

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