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Cited by 207

The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.

Informatics Platform for Global Proteomic Profiling and Biomarker Discovery Using Liquid Chromatography-Tandem Mass Spectrometry

Open access
Radulovic, Dragan, Jelveh, Salomeh, Ryu, Soyoung, Hamilton, T. Guy, Foss, Eric, Mao, Yongyi, Emili, Andrew·2004·Molecular & Cellular Proteomics

Abstract

We have developed an integrated suite of algorithms, statistical methods, and computer applications to support large-scale LC-MS-based gel-free shotgun profiling of complex protein mixtures using basic experimental procedures. The programs automatically detect and quantify large numbers of peptide peaks in feature-rich ion mass chromatograms, compensate for spurious fluctuations in peptide signal intensities and retention times, and reliably match related peaks across many different datasets. Application of this toolkit markedly facilitates pattern recognition and biomarker discovery in global comparative proteomic studies, simplifying mechanistic investigation of physiological responses and the detection of proteomic signatures of disease.

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Crossref · 10.1074/mcp.m400061-mcp200

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Metadata

Authors
Radulovic, D., Jelveh, S., Ryu, S., Hamilton, T. G., Foss, E., Mao, Y., & Emili, A.
Venue
Molecular & Cellular Proteomics
Publisher
Elsevier BV
Published
2004-10
Volume
3
Issue
10
Pages
984-997
ISSN
1535-9476 (ISSN-L)
OpenAlex
W2167443016
Cited by
207
References
3
FWCI
10.53
Type
journal article
Language
en
Open access
hybrid

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CoChat. (2026). Citation check: Informatics Platform for Global Proteomic Profiling and Biomarker Discovery Using Liquid Chromatography-Tandem Mass Spectrometry. https://app.cochat.ai/papers/10.1074/mcp.m400061-mcp200
The paper
Radulovic, D., Jelveh, S., Ryu, S., Hamilton, T. G., Foss, E., Mao, Y., & Emili, A. (2004). Informatics Platform for Global Proteomic Profiling and Biomarker Discovery Using Liquid Chromatography-Tandem Mass Spectrometry. Molecular & Cellular Proteomics. https://doi.org/10.1074/mcp.m400061-mcp200

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.