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Data Analysis of Discrete-Valued Models for Genetic Sequences

In: Quantitative Methods and Data Analysis in Applied Demography - Volume 2

Author

Listed:
  • Valeriy Voloshko

    (Belarusian State University
    Research Institute for Applied Problems of Mathematics and Informatics)

  • Yuriy Kharin

    (Belarusian State University
    Research Institute for Applied Problems of Mathematics and Informatics)

Abstract

Two families of parsimonious Markov models for statistical analysis of genetic sequences are considered. The first family of conditionally nonlinear autoregressive (CNAR) models is useful in such problems as detection and description of deep Markov dependencies in long genetic sequences and recognition of protein coding regions. The second family of maximum entropy models (MEM) is useful in problem of discrimination of special human DNA signals (donor and acceptor splice sites, start codon, stop codon) from decoys.

Suggested Citation

  • Valeriy Voloshko & Yuriy Kharin, 2025. "Data Analysis of Discrete-Valued Models for Genetic Sequences," The Springer Series on Demographic Methods and Population Analysis, in: Christos H. Skiadas & Charilaos Skiadas (ed.), Quantitative Methods and Data Analysis in Applied Demography - Volume 2, chapter 0, pages 183-198, Springer.
    • Handle: RePEc:spr:ssdmcp:978-3-031-82279-7_15
    DOI: 10.1007/978-3-031-82279-7_15
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