Bioinformatics Methods for Mass Spectrometry-Based Proteomics Data Analysis
Clicks: 92
ID: 171470
2020
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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chen2020bioinformaticsinternational
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| Authors | Chen, Chen;Hou, Jie;Tanner, John J.;Cheng, Jianlin; |
| Journal | International journal of molecular sciences |
| Year | 2020 |
| DOI | DOI not found |
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| Keywords |
chemistry
Therapeutics. Pharmacology
Biology (General)
Medicine
Chemical technology
Computer applications to medicine. Medical informatics
Science (General)
Mechanical engineering and machinery
Science
neurosciences. biological psychiatry. neuropsychiatry
mathematics
electronic computers. computer science
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