IPeak: An open source tool to combine results from multiple MS/MS search engines

The OMSSAPercolator: An automated tool to validate OMSSA results

(2014) Bo Wen et al.   PROTEOMICS

MS-GF+ makes progress towards a universal database search tool for proteomics

(2014) Sangtae Kim et al.   Nature Communications

Fast and Accurate Database Searches with MS-GF+Percolator

(2013) Viktor Granholm et al.   JOURNAL OF PROTEOME RESEARCH

Combining Percolator with X!Tandem for Accurate and Sensitive Peptide Identification

(2013) Mingguo Xu et al.   JOURNAL OF PROTEOME RESEARCH

Tools (Viewer, Library and Validator) that Facilitate Use of the Peptide and Protein Identification Standard Format, Termed mzIdentML

(2013) Fawaz Ghali et al.   MOLECULAR & CELLULAR PROTEOMICS

jmzIdentML API: A Java interface to the mzIdentML standard for peptide and protein identification data

(2012) Florian Reisinger et al.   PROTEOMICS

On Using Samples of Known Protein Content to Assess the Statistical Calibration of Scores Assigned to Peptide-Spectrum Matches in Shotgun Proteomics

(2011) Viktor Granholm et al.   JOURNAL OF PROTEOME RESEARCH

MSblender: A Probabilistic Approach for Integrating Peptide Identifications from Multiple Database Search Engines

(2011) Taejoon Kwon et al.   JOURNAL OF PROTEOME RESEARCH

iProphet: Multi-level Integrative Analysis of Shotgun Proteomic Data Improves Peptide and Protein Identification Rates and Error Estimates

(2011) David Shteynberg et al.   MOLECULAR & CELLULAR PROTEOMICS

XTandem Parser: An open-source library to parse and analyse X!Tandem MS/MS search results

(2010) Thilo Muth et al.   PROTEOMICS

Accurate and Sensitive Peptide Identification with Mascot Percolator

(2009) Markus Brosch et al.   JOURNAL OF PROTEOME RESEARCH

OMSSA Parser: An open-source library to parse and extract data from OMSSA MS/MS search results

(2009) Harald Barsnes et al.   PROTEOMICS

Improving sensitivity in proteome studies by analysis of false discovery rates for multiple search engines

(2009) Andrew R. Jones et al.   PROTEOMICS

An Unsupervised, Model-Free, Machine-Learning Combiner for Peptide Identifications from Tandem Mass Spectra

(2009) Nathan Edwards et al.   Clinical Proteomics

Improving Sensitivity by Probabilistically Combining Results from Multiple MS/MS Search Methodologies

(2008) Brian C. Searle et al.   JOURNAL OF PROTEOME RESEARCH