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Martin McIntosh

dblp:53/1996 · DBLP profile ↗
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2ranked-venue papers
0as first author
0since 2021 · last 2006
0009-0007-3672-7489ORCID · corroborated

Domains — the database's venue-derived domains; a paper can count in several

Applied, interdisciplinary, general and emerging computing · 2

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Interdisciplinary, comprehensive, and emerging computing
2 papers
Bioinformatics and computational biology · 100%

Topics — the 6 heaviest of 6, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Bioinformatics and computational biology
proteomics
0.122006
General framework for developing and evaluating database scoring algorithms using the TANDEM search engine · Bioinform. 2006
A suite of algorithms for the comprehensive analysis of complex protein mixtures using high-resolution LC-MS · Bioinform. 2006
Bioinformatics and computational biology › metabolomics
LC-MS data analysis
0.112006
A suite of algorithms for the comprehensive analysis of complex protein mixtures using high-resolution LC-MS · Bioinform. 2006
Bioinformatics and computational biology › proteomics
mass spectrometry data analysis
0.112006
General framework for developing and evaluating database scoring algorithms using the TANDEM search engine · Bioinform. 2006
Bioinformatics and computational biology › proteomics › peptide identification
peptide-spectrum match scoring
0.112006
General framework for developing and evaluating database scoring algorithms using the TANDEM search engine · Bioinform. 2006
Bioinformatics and computational biology › proteomics › quantitative proteomics
label-free quantification
0.012006
A suite of algorithms for the comprehensive analysis of complex protein mixtures using high-resolution LC-MS · Bioinform. 2006
Bioinformatics and computational biology › proteomics › quantitative proteomics
peptide quantification
0.012006
A suite of algorithms for the comprehensive analysis of complex protein mixtures using high-resolution LC-MS · Bioinform. 2006

Methods — techniques the papers use, named apart from their topics

pluggable scoring architecture · 0.1peptide feature detection · 0.1normalization · 0.1alignment · 0.1
YearPublicationVenuePosition
2006 A suite of algorithms for the comprehensive analysis of complex protein mixtures using high-resolution LC-MS
abstract
MOTIVATION: Comparing two or more complex protein mixtures using liquid chromatography mass spectrometry (LC-MS) requires multiple analysis steps to locate and quantitate natural peptides within a single experiment and to align and normalize findings across multiple experiments. RESULTS: We describe msInspect, an open-source application comprising algorithms and visualization tools for the analysis of multiple LC-MS experimental measurements. The platform integrates novel algorithms for detecting signatures of natural peptides within a single LC-MS measurement and combines multiple experimental measurements into a peptide array, which may then be mined using analysis tools traditionally applied to genomic array analysis. The platform supports quantitation by both label-free and isotopic labeling approaches. The software implementation has been designed so that many key components may be easily replaced, making it useful as a workbench for integrating other novel algorithms developed by a growing research community. AVAILABILITY: The msInspect software is distributed freely under an Apache 2.0 license. The software as well as a Zip file with all peptide feature files and scripts needed to generate the tables and figures in this article are available at http://proteomics.fhcrc.org/.
Matthew Bellew, Marc Coram, Matthew Fitzgibbon, Mark Igra, Timothy W. Randolph 0002, Pei Wang 0014, Damon May, Jimmy K. Eng, Ruihua Fang, ChenWei Lin, Jinzhi Chen, David Goodlett, Jeffrey Whiteaker, Amanda G. Paulovich, Martin McIntosh
Bioinform.15
2006 General framework for developing and evaluating database scoring algorithms using the TANDEM search engine
abstract
MOTIVATION: Tandem mass spectrometry (MS/MS) identifies protein sequences using database search engines, at the core of which is a score that measures the similarity between peptide MS/MS spectra and a protein sequence database. The TANDEM application was developed as a freely available database search engine for the proteomics research community. To extend TANDEM as a platform for further research on developing improved database scoring methods, we modified the software to allow users to redefine the scoring function and replace the native TANDEM scoring function while leaving the remaining core application intact. Redefinition is performed at run time so multiple scoring functions are available to be selected and applied from a single search engine binary. We introduce the implementation of the pluggable scoring algorithm and also provide implementations of two TANDEM compatible scoring functions, one previously described scoring function compatible with PeptideProphet and one very simple scoring function that quantitative researchers may use to begin their development. This extension builds on the open-source TANDEM project and will facilitate research into and dissemination of novel algorithms for matching MS/MS spectra to peptide sequences. The pluggable scoring schema is also compatible with related search applications P3 and Hunter, which are part of the X! suite of database matching algorithms. The pluggable scores and the X! suite of applications are all written in C++. AVAILABILITY: Source code for the scoring functions is available from http://proteomics.fhcrc.org
Brendan MacLean, Jimmy K. Eng, Ronald C. Beavis, Martin McIntosh
Bioinform.4