Abstract
With the rapid development of high-throughput techniques, mass spectrometry has been widely used for large-scale protein analysis. To search for the existing proteins, discover biomarkers, and diagnose and prognose diseases, machine learning methods are applied in mass spectrometry data analysis. This paper reviews the applications of five kinds of machine learning methods to mass spectrometry data analysis from an algorithmic point of view, including support vector machine, decision tree, random forest, naive Bayesian classifier and deep learning.
Keywords: Mass spectrometry, high-throughput technique, machine learning, deep learning, computational proteomics, protein identification.
Current Proteomics
Title:Machine Learning for Mass Spectrometry Data Analysis in Proteomics
Volume: 18 Issue: 5
Author(s): Juntao Li, Kanglei Zhou* Bingyu Mu*
Affiliation:
- School of Computer Science and Engineering, Beihang University, Beijing,China
- College of Arts and Design, Zhengzhou University of Light Industry, Zhengzhou,China
Keywords: Mass spectrometry, high-throughput technique, machine learning, deep learning, computational proteomics, protein identification.
Abstract: With the rapid development of high-throughput techniques, mass spectrometry has been widely used for large-scale protein analysis. To search for the existing proteins, discover biomarkers, and diagnose and prognose diseases, machine learning methods are applied in mass spectrometry data analysis. This paper reviews the applications of five kinds of machine learning methods to mass spectrometry data analysis from an algorithmic point of view, including support vector machine, decision tree, random forest, naive Bayesian classifier and deep learning.
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Cite this article as:
Li Juntao , Zhou Kanglei*, Mu Bingyu *, Machine Learning for Mass Spectrometry Data Analysis in Proteomics, Current Proteomics 2021; 18 (5) . https://dx.doi.org/10.2174/1570164617999201023145304
DOI https://dx.doi.org/10.2174/1570164617999201023145304 |
Print ISSN 1570-1646 |
Publisher Name Bentham Science Publisher |
Online ISSN 1875-6247 |
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Mass spectrometry data acquisition and analysis for proteomics
The Thematic Issue on "Mass spectrometry data acquisition and analysis for proteomics" aims to explore the latest advancements and challenges in the field of proteomics through the lens of mass spectrometry. Proteomics, the large-scale study of proteins and their functions, plays a crucial role in understanding various biological processes and ...read more
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