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Matematicheskaya Biologiya i Bioinformatika, 2014, Volume 9, Issue 1, Pages 33–62
(Mi mbb171)
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This article is cited in 3 scientific papers (total in 3 papers)
Comments
Spectral-Statistical Approach to Latent Profile Periodicity Recognition in DNA Sequences
V. A. Kutyrkina, M. B. Chaleyb a Moscow State Technical University n.a. N. E. Bauman, Moscow, 107005, Russia
b Institute of Mathematical Problems of Biology, Russian Academy of Sciences, Pushchino, 142290, Russia
Abstract:
Earlier, a new notion of latent profile periodicity was introduced by the authors of present work. In 2013 in the “Mathematical biology and bioinformatics” journal an article was published, where a method for recognizing latent periodicity of such a new type was described. This method is based on employing spectral-statistical approach (2S-approach) to DNA sequences analysis. Efficiency of the elaborated method was shown, and a comparison with other known methods was done, particularly with information decomposition method (ID-method). In reply to the publication, the ID-method developers published a commentary in the journal. The commentary criticized the latent profile periodicity recognition method based on the 2S-approach. As follows from the commentary, its authors either did not read our article attentively or they are not aware of some notions of mathematical apparatus used in the article. So, we believe it is necessary to clarify once more the theoretical fundamentals of our method and to draw attention to key moments of its application, which have not been appreciated by our opponents. Moreover in the present work it is shown that the ID-method, contrary to the 2S-approach, is not a sustainable technique for revealing latent periodicity in DNA sequences, what can lead to incorrectness of its results.
Key words:
latent periodicity, spectral-statistical approach, latent profile periodicity.
Received 29.12.2013, Published 29.01.2014
Citation:
V. A. Kutyrkin, M. B. Chaley, “Spectral-Statistical Approach to Latent Profile Periodicity Recognition in DNA Sequences”, Mat. Biolog. Bioinform., 9:1 (2014), 33–62
Linking options:
https://www.mathnet.ru/eng/mbb171 https://www.mathnet.ru/eng/mbb/v9/i1/p33
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Abstract page: | 306 | Full-text PDF : | 86 | References: | 71 |
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