Data Analysis of Discrete-Valued Models for Genetic Sequences

Valeriy Voloshko () and Yuriy Kharin ()
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Valeriy Voloshko: Belarusian State University
Yuriy Kharin: Belarusian State University

Chapter Chapter 15 in Quantitative Methods and Data Analysis in Applied Demography - Volume 2, 2025, pp 183-198 from Springer

Abstract: 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.

Keywords: Data analysis; Discrete data; Markov model; Parsimony; Genetic sequence (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:spr:ssdmcp:978-3-031-82279-7_15

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DOI: 10.1007/978-3-031-82279-7_15

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