Selecting informative features of human gene exons

  • Andrei V. Volkau Belarusian State University, 4 Niezaliežnasci Avenue, Minsk 220030, Belarus
  • Mikalai M. Yatskou Belarusian State University, 4 Niezaliežnasci Avenue, Minsk 220030, Belarus
  • Vasily V. Grinev Belarusian State University, 4 Niezaliežnasci Avenue, Minsk 220030, Belarus
DOI: https://doi.org/10.33581/2520-6508-2019-1-77-89

Abstract

Dimensionality reduction of the human gene exon feature space is considered with the aim of gene identification. To evaluate the performance of various feature selection algorithms, computational experiments were carried out using the examples of exons of 14 known human genes. It is proven that exons are clearly separable regarding gene affiliation. Feature selection algorithms are sensitive to noise features and allow to estimate their number. Reducing the number of features improves CPU-time, memory usage as well as reduces the complexity of a model and makes it easier to interpret. Our findings indicate that utilizing of features of flanking intronic sequences leads to better prediction models in comparison with utilizing of exon features. The results of the research provide new opportunities for study of human gene data using machine learning algorithms.

Author Biographies

Andrei V. Volkau, Belarusian State University, 4 Niezaliežnasci Avenue, Minsk 220030, Belarus

postgraduate student at the department of system analysis and computer simulation, faculty of radiophysics and computer technologies

Mikalai M. Yatskou, Belarusian State University, 4 Niezaliežnasci Avenue, Minsk 220030, Belarus

PhD (physics and mathematics), docent; associate professor at the department of system analysis and computer simulation, faculty of radiophysics and computer technologies

Vasily V. Grinev, Belarusian State University, 4 Niezaliežnasci Avenue, Minsk 220030, Belarus

PhD (biology), docent; associate professor at the department of genetics, faculty of biology

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Published
2019-04-08
Keywords: exon, intron, bioinformatics, feature selection, simulation modeling, classification algorithm
How to Cite
Volkau, A. V., Yatskou, M. M., & Grinev, V. V. (2019). Selecting informative features of human gene exons. Journal of the Belarusian State University. Mathematics and Informatics, 1, 77-89. https://doi.org/10.33581/2520-6508-2019-1-77-89
Issue
No 1 (2019): Journal of the Belarusian State University. Mathematics and Informatics
Section
Theoretical Foundations of Computer Science

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