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Statistical methods for detecting latent periodicity patterns in biological sequences: The case of small-size samples

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Abstract

An original spectral-statistical approach for detecting latent periodicity in biological sequences is proposed. This approach can be applied under conditions of limited statistical sample. It allows one to avoid redundancy and instability when identifying the latent periodicity structure. The optimality of the periodicity-pattern-size estimates obtained for approximate tandem repeats on the basis of the spectral-statistical approach is demonstrated in practical examples.

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Authors and Affiliations

  1. Institute of Mathematical Biology Problems, Russian Academy of Sciences, Institutskaya ul. 4, Pushchino, Moscow oblast, Russia

    M. B. Chaley & N. N. Nazipova

  2. Moscow State Technical University n.a. N.E. Bauman, ul. Vtoraya Baumanskaya 5, Moscow, 107005, Russia

    V. A. Kutyrkin

Authors
  1. M. B. Chaley
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  2. N. N. Nazipova
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  3. V. A. Kutyrkin
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Correspondence to M. B. Chaley.

Additional information

Maria Borisovna Chaley was born in 1963 and graduated from the Moscow Institute of Physics and Technology in 1988 (M.Sc.). She received her PhD in biophysics in 1993 and became a docent in bioinformatics in 2003. At the present time, she is a senior research fellow at the Institute of Mathematical Biology Problems of the Russian Academy of Sciences. Her research interests include bioinformatics, genetic text analysis, and molecular evolution. She is the author of over 40 research publications, including 14 journal articles.

Nafisa Nailovna Nazipova was born in 1960 and graduated from the Department of Computational Mathematics and Cybernetics of Lenin Kazan State University in 1982 (MSc.). She received her PhD in physics and mathematics (mathematic modeling, numerical methods, and program complexes) in 2002. At the present time, she is the head of the bioinformatics laboratory at the Institute of Mathematical Biology Problems of the Russian Academy of Sciences. Her research interests include bioinformatics and the structural and functional organization of genetic sequences. She is the author of over 35 research publications, including 9 papers in refereed journals and 2 book chapters.

Vladimir Andreyevich Kutyrkin was born in 1952 and graduated from the Department of Mechanics and Mathematics of Lomonosov Moscow State University in 1974 (MSc.). He received his PhD in physics and mathematics in 1995. At the present time, he is a docent of Bauman Moscow State Technical University. His research interests include applied mathematical statistics, computational and discrete mathematics, and bioinformatics. He is the author of over 20 research publications, including 11 journal papers.

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Chaley, M.B., Nazipova, N.N. & Kutyrkin, V.A. Statistical methods for detecting latent periodicity patterns in biological sequences: The case of small-size samples. Pattern Recognit. Image Anal. 19, 358–367 (2009). https://doi.org/10.1134/S1054661809020217

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