article

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Authors:

Rafał Biedrzycki,

Jarosław ArabasAuthors Info & Claims

International Journal of Applied Mathematics and Computer Science, Volume 22, Issue 3

Pages 711 - 721

Published: 01 September 2012 Publication History

Abstract

AbstractThis paper presents an application of methods from the machine learning domain to solving the task of DNA sequence recognition. We present an algorithm that learns to recognize groups of DNA sequences sharing common features such as sequence functionality. We demonstrate application of the algorithm to find splice sites, i.e., to properly detect donor and acceptor sequences. We compare the results with those of reference methods that have been designed and tuned to detect splice sites. We also show how to use the algorithm to find a human readable model of the IRE Iron-Responsive Element and to find IRE sequences. The method, although universal, yields results which are of quality comparable to those obtained by reference methods. In contrast to reference methods, this approach uses models that operate on sequence patterns, which facilitates interpretation of the results by humans.

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Cited By

Bogdanowicz DGiaro K(2018)On a matching distance between rooted phylogenetic treesInternational Journal of Applied Mathematics and Computer Science10.2478/amcs-2013-005023:3(669-684)Online publication date: 15-Dec-2018
https://dl.acm.org/doi/10.2478/amcs-2013-0050
Mandal I(2018)A novel approach for predicting DNA splice junctions using hybrid machine learning algorithmsSoft Computing - A Fusion of Foundations, Methodologies and Applications10.1007/s00500-014-1550-z19:12(3431-3444)Online publication date: 30-Dec-2018
https://dl.acm.org/doi/10.1007/s00500-014-1550-z

KIS
1. Applied computing
  1. Life and medical sciences
2. Computing methodologies
  1. Machine learning
    1. Learning paradigms
      1. Supervised learning

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Information & Contributors

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cover image International Journal of Applied Mathematics and Computer Science

International Journal of Applied Mathematics and Computer Science Volume 22, Issue 3

09 2012

267 pages

EISSN:2083-8492

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Publisher

Walter de Gruyter & Co.

United States

Publication History

Published: 01 September 2012

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Cited By

Bogdanowicz DGiaro K(2018)On a matching distance between rooted phylogenetic treesInternational Journal of Applied Mathematics and Computer Science10.2478/amcs-2013-005023:3(669-684)Online publication date: 15-Dec-2018
https://dl.acm.org/doi/10.2478/amcs-2013-0050
Mandal I(2018)A novel approach for predicting DNA splice junctions using hybrid machine learning algorithmsSoft Computing - A Fusion of Foundations, Methodologies and Applications10.1007/s00500-014-1550-z19:12(3431-3444)Online publication date: 30-Dec-2018
https://dl.acm.org/doi/10.1007/s00500-014-1550-z

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