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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Complete De Novo Assembly of Monoclonal Antibody Sequences
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Challenges and Opportunities in Proteomics Data Analysis
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Metabolomics Data Normalization with EigenMS
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DirecTag: Accurate Sequence Tags from Peptide MS/MS through Statistical Scoring
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Automated identification of SUMOylation sites using mass spectrometry and SUMmOn pattern recognition software
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Efficient Marginalization to Compute Protein Posterior Probabilities from Shotgun Mass Spectrometry Data
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MSPLIT-DIA: sensitive peptide identification for data-independent acquisition
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Accurate Peptide Fragment Mass Analysis: Multiplexed Peptide Identification and Quantification
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Quantitative Phosphoproteome Analysis of Bacillus subtilis Reveals Novel Substrates of the Kinase PrkC and Phosphatase PrpC
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DBParser: Web-Based Software for Shotgun Proteomic Data Analyses
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The Phosphoproteome of the Minimal Bacterium Mycoplasma pneumoniae
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Machine Learning-based Classification of Diffuse Large B-cell Lymphoma Patients by Their Protein Expression Profiles
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A Statistical Model for iTRAQ Data Analysis
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A Bayesian Approach to Protein Inference Problem in Shotgun Proteomics
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The SEQUEST Family Tree
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De Novo Analysis of Peptide Tandem Mass Spectra by Spectral Graph Partitioning
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MassSieve: Panning MS/MS peptide data for proteins
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An Unsupervised, Model-Free, Machine-Learning Combiner for Peptide Identifications from Tandem Mass Spectra
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ADVANCEMENT IN PROTEIN INFERENCE FROM SHOTGUN PROTEOMICS USING PEPTIDE DETECTABILITY
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Elimination of Systematic Mass Measurement Errors in Liquid Chromatography−Mass Spectrometry Based Proteomics Using Regression Models and a Priori Partial Knowledge of the Sample Content
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Systematic Analysis of Mycobacterial Acylation Reveals First Example of Acylation-mediated Regulation of Enzyme Activity of a Bacterial Phosphatase
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Estimation of Missing Values Using a Weighted K-Nearest Neighbors Algorithm
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Protein quantification across hundreds of experimental conditions
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A Decoy-Free Approach to the Identification of Peptides
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Nε- and O-Acetylation in Mycobacterium tuberculosis Lineage 7 and Lineage 4 Strains: Proteins Involved in Bioenergetics, Virulence, and Antimicrobial Resistance Are Acetylated
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Unveiling the Novel Dual Specificity Protein Kinases in Bacillus anthracis
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Acetylome profiling of Vibrio alginolyticus reveals its role in bacterial virulence
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Phosphoproteomics-Based Profiling of Kinase Activities in Cancer Cells
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Integrative Analysis of Metabolomic, Proteomic and Genomic Data to Reveal Functional Pathways and Candidate Genes for Drip Loss in Pigs
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ProteomeGenerator: A Framework for Comprehensive Proteomics Based on de Novo Transcriptome Assembly and High-Accuracy Peptide Mass Spectral Matching
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Preview: A Program for Surveying Shotgun Proteomics Tandem Mass Spectrometry Data
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Param-Medic: A Tool for Improving MS/MS Database Search Yield by Optimizing Parameter Settings
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Evaluation of linear models and missing value imputation for the analysis of peptide-centric proteomics
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Substrate-based kinase activity inference identifies MK2 as driver of colitis
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Quantitative Proteomic Analysis of Membrane Proteins Involved in Astroglial Differentiation of Neural Stem Cells by SILAC Labeling Coupled with LC–MS/MS
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Distribution-free multiple imputation in an interaction matrix through singular value decomposition
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Combining High-Resolution and Exact Calibration To Boost Statistical Power: A Well-Calibrated Score Function for High-Resolution MS2 Data
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A Proteomics-Based Approach Reveals Differential Regulation of Urine Proteins between Metabolically Healthy and Unhealthy Obese Patients
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Systematic Affinity Purification Coupled to Mass Spectrometry Identified p62 as Part of the Cannabinoid Receptor CB2 Interactome
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Support Vector Machines for Improved Peptide Identification from Tandem Mass Spectrometry Database Search
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Network Analysis of Se-and Zn-related Proteins in the Serum Proteomics Expression Profile of the Endemic Dilated Cardiomyopathy Keshan Disease
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BioID Combined with Mass Spectrometry to Study Herpesvirus Protein–Protein Interaction Networks
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Integration of RNA-Seq and RPPA data for survival time prediction in cancer patients
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Impact of High Salt Diet on Cerebral Vascular Function and Stroke in Tff3−/−/C57BL/6N Knockout and WT (C57BL/6N) Control Mice
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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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