Biomedical subjects

John P Cortens

Publications and source records attributed to John P Cortens.

3 recordsLinked to original sources

PubMed2006

Use of peptide retention time prediction for protein identification by off-line reversed-phase HPLC-MALDI MS/MS.

A new algorithm, sequence-specific retention calculator, was developed to predict retention time of tryptic peptides during RP HPLC fractionation on C18, 300-A pore size columns. Correlations of up to approximately 0.98 R2 value were obtained for a test library of approximately 2000 peptides and approximately 0.95-0.97 for a variety of real samples. The algorithm was applied in conjunction with an exclusion protocol based on mass (15 ppm tolerance) and retention time (2-min tolerance for 0.66% acetonitrile/min gradient), MART criteria to significantly reduce the instrument time required for complete MS/MS analysis of a digest separated by RP HPLC. This was confirmed by reanalyzing the set of HPLC-MALDI MS/MS data with no loss in protein identifications, despite the number of virtually executed MS/MS analyses being decreased by 57%.

Cell Line, Tumor↗

PubMed2005

The use of proteotypic peptide libraries for protein identification.

This paper describes an algorithm to apply proteotypic peptide sequence libraries to protein identifications performed using tandem mass spectrometry (MS/MS). Proteotypic peptides are those peptides in a protein sequence that are most likely to be confidently observed by current MS-based proteomics methods. Libraries of proteotypic peptide sequences were compiled from the Global Proteome Machine Database for Homo sapiens and Saccharomyces cerevisiae model species proteomes. These libraries were used to scan through collections of tandem mass spectra to discover which proteins were represented by the data sets, followed by detailed analysis of the spectra with the full protein sequences corresponding to the discovered proteotypic peptides. This algorithm (Proteotypic Peptide Profiling, or P3) resulted in sequence-to-spectrum matches comparable to those obtained by conventional protein identification algorithms using only full protein sequences, with a 20-fold reduction in the time required to perform the identification calculations. The proteotypic peptide libraries, the open source code for the implementation of the search algorithm and a website for using the software have been made freely available. Approximately 4% of the residues in the H. sapiens proteome were required in the proteotypic peptide library to successfully identify proteins.

Algorithms↗

PubMedDate not supplied

Open source system for analyzing, validating, and storing protein identification data.

This paper describes an open-source system for analyzing, storing, and validating proteomics information derived from tandem mass spectrometry. It is based on a combination of data analysis servers, a user interface, and a relational database. The database was designed to store the minimum amount of information necessary to search and retrieve data obtained from the publicly available data analysis servers. Collectively, this system was referred to as the Global Proteome Machine (GPM). The components of the system have been made available as open source development projects. A publicly available system has been established, comprised of a group of data analysis servers and one main database server.

Computational Biology↗