Machine Learning in Biology
- Authors: Taskina A.K1,2, Muravyova A.A1,2, Elsukova A.S1,2, Fishman V.S1,2
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Affiliations:
- Institute of Cytology and Genetics, Siberian Branch of RAS
- Novosibirsk State University
- Issue: No 9 (2020)
- Pages: 3-17
- Section: Articles
- URL: https://journals.eco-vector.com/0032-874X/article/view/627917
- DOI: https://doi.org/10.7868/S0032874X2009001X
- ID: 627917
Cite item
Abstract
The increase of experimental data at the beginning of the XXI century coincided with the revolution in machine learning methods, which began to be actively used for solving biological problems. The main advantage of machine learning is the ability to formulate and test many hypotheses based on large datasets from modern experiments. The article discusses several machine learning algorithms and examples of their practical application in genetics and genomics.
Keywords
About the authors
A. K Taskina
Institute of Cytology and Genetics, Siberian Branch of RAS; Novosibirsk State UniversityNovosibirsk, Russia
A. A Muravyova
Institute of Cytology and Genetics, Siberian Branch of RAS; Novosibirsk State UniversityNovosibirsk, Russia
A. S Elsukova
Institute of Cytology and Genetics, Siberian Branch of RAS; Novosibirsk State UniversityNovosibirsk, Russia
V. S Fishman
Institute of Cytology and Genetics, Siberian Branch of RAS; Novosibirsk State University
Email: minja-f@ya.ru
Novosibirsk, Russia
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Supplementary files
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