On the entropy of DNA: algorithms and measurements based on memory and rapid convergence
Proceedings of the sixth annual ACM-SIAM symposium on Discrete algorithms
Identifying statistical dependence in genomic sequences via mutual information estimates
EURASIP Journal on Bioinformatics and Systems Biology
Computational Statistics & Data Analysis
Kernel-based machine learning for fast text mining in R
Computational Statistics & Data Analysis
Serial dependence of NDARMA processes
Computational Statistics & Data Analysis
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The statistical structure of DNA sequences is of great interest to molecular biology, genetics and the theory of evolution. One popular approach is sequence modeling using Markov processes of different orders, and further statistical estimation of their parameters. To continue the investigations according to this approach, tests for hypothesis testing are used to estimate the ''memory'' (or connectivity) of genetic texts and to solve the DNA-based problem relating to the phylogenetic system of various groups of organisms.