The rise and fall of machine learning methods in biomedical research

In the era of explosion in biological data, machine learning techniques are becoming more popular in life sciences, including biology and medicine. This research note examines the rise and fall of the most commonly used machine learning techniques in life sciences over the past three decades.

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Bibliographic Details
Published inF1000 research Vol. 6; p. 2012
Main Author Koohy, Hashem
Format Journal Article
LanguageEnglish
Published England Faculty of 1000 Ltd 2017
F1000 Research Limited
F1000 Research Ltd
Subjects
Artificial intelligence
Bioinformatics
Biomedical research
Gene expression
Genomes
Genomics
Learning algorithms
Life sciences
Neural networks
Popularity
Principal components analysis
Research Note
Software
Statistical Methodologies & Health Informatics
Studies
United Kingdom > UK
support vector machine
linear regression
hierarchical clustering
t-SNE
random forest
machine learning
principal component
deep neural network
Online AccessGet full text
ISSN2046-1402
2046-1402
DOI10.12688/f1000research.13016.2

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Summary:In the era of explosion in biological data, machine learning techniques are becoming more popular in life sciences, including biology and medicine. This research note examines the rise and fall of the most commonly used machine learning techniques in life sciences over the past three decades.
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No competing interests were disclosed.
ISSN:2046-1402
2046-1402
DOI:10.12688/f1000research.13016.2