Bioinformatics Methods for Mass Spectrometry-Based Proteomics Data Analysis

Clicks: 117
ID: 171470
2020
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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.
Reference Key
chen2020bioinformaticsinternational Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Chen, Chen;Hou, Jie;Tanner, John J.;Cheng, Jianlin;
Journal International journal of molecular sciences
Year 2020
DOI
DOI not found
URL
https://www.mdpi.com/1422-0067/21/8/2873
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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