Cited by 283Advanced Proteomics Techniques and ApplicationsBioinformatics and Genomic NetworksMass Spectrometry Techniques and Applications

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Bioinformatics Methods for Mass Spectrometry-Based Proteomics Data Analysis

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Chen, Chen, Hou, Jie, Tanner, John J., Cheng, Jianlin·2020·International Journal of Molecular Sciences

DOI 10.3390/ijms21082873PMC PMC7216093

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Abstract

Recent advances in mass spectrometry (MS)-based proteomics have enabled tremendous progress in the understanding of cellular mechanisms, disease progression, and the relationship between genotype and phenotype. Though many popular bioinformatics methods in proteomics are derived from other omics studies, novel analysis strategies are required to deal with the unique characteristics of proteomics data. In this review, we discuss the current developments in the bioinformatics methods used in proteomics and how they facilitate the mechanistic understanding of biological processes. We first introduce bioinformatics software and tools designed for mass spectrometry-based protein identification and quantification, and then we review the different statistical and machine learning methods that have been developed to perform comprehensive analysis in proteomics studies. We conclude with a discussion of how quantitative protein data can be used to reconstruct protein interactions and signaling networks.

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Authors: Chen, C., Hou, J., Tanner, J. J., & Cheng, J.
Affiliations: University of Missouri (US)
Saint Louis University (US)
Corresponding author: Cheng, Jianlin
ORCID: Chen, Chen
Hou, Jie
Tanner, John J.
Cheng, Jianlin
Venue: International Journal of Molecular Sciences
Publisher: MDPI AG
Published: 2020-04-20
Volume: 21
Issue: 8
Pages: 2873
ISSN: 1422-0067 (ISSN-L)
DOI: 10.3390/ijms21082873
PMC: PMC7216093
OpenAlex: W3016487203
Cited by: 280
References: 192
Citations by year: 2026: 22 · 2025: 58 · 2024: 56 · 2023: 51 · 2022: 54 · 2021: 33 · 2020: 6
FWCI: 4.31
Type: journal article
Language: en
Open access: gold
dx.doi.org
Licence: cc-by
creativecommons.org/licenses/by/4.0/ (vor)
Locations: International Journal of Molecular Sciences (publishedVersion, cc-by)
PubMed Central (publishedVersion, cc-by)
PubMed (publishedVersion)
DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
Funders: National Institutes of Health (R01GM093123)
National Science Foundation (DBI1759934, IIS1763246)
Topics: Physical Sciences › Chemistry › Spectroscopy › Advanced Proteomics Techniques and Applications
Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Bioinformatics and Genomic Networks
Physical Sciences › Chemistry › Spectroscopy › Mass Spectrometry Techniques and Applications
Keywords: proteomics data analysis, mass spectrometry, protein identification, protein quantification, bioinformatics software, statistical analysis, machine learning, protein-protein interaction network, signaling networks, quantitative proteomics
MeSH terms: Machine Learning, Data Analysis, Humans, Mass Spectrometry, Computational Biology, Protein Interaction Mapping, Proteomics, Workflow, Protein Interaction Maps

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Bioinformatics Methods for Mass Spectrometry-Based Proteomics Data Analysis

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