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Cited by 595

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ProFound: An Expert System for Protein Identification Using Mass Spectrometric Peptide Mapping Information

Zhang, Wenzhu, Chait, Brian T.·2000·Analytical Chemistry

Abstract

We describe the protein search engine "ProFound", which employs a Bayesian algorithm to identify proteins from protein databases using mass spectrometric peptide mapping data. The algorithm ranks protein candidates by taking into account individual properties of each protein in the database as well as other information relevant to the peptide mapping experiment. The program consistently identifies the correct protein(s) even when the data quality is relatively low or when the sample consists of a simple mixture of proteins. Illustrative examples of protein identifications are provided.

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Metadata

Authors
Zhang, W., & Chait, B. T.
Venue
Analytical Chemistry
Published
2000-05-04
Volume
72
Issue
11
Pages
2482-2489
ISSN
  • 0003-2700 (ISSN-L)
  • 1520-6882
OpenAlex
W1985560593
Cited by
595
References
1
FWCI
22.59
Type
journal article
Language
en
Open access
closed

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CoChat. (2026). Citation check: ProFound: An Expert System for Protein Identification Using Mass Spectrometric Peptide Mapping Information. https://app.cochat.ai/papers/10.1021/ac991363o
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Zhang, W., & Chait, B. T. (2000). ProFound: An Expert System for Protein Identification Using Mass Spectrometric Peptide Mapping Information. Analytical Chemistry. https://doi.org/10.1021/ac991363o

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