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
Many of the same modeling methods used in natural languages, specifically Markov models and HMM\u27s...
S.S. and M.S.B. acknowledge the Engineering and Physical Sciences Research Council (EPSRC), grant re...
The research of Gene Predicting Algorithms is a key section in bioinformatics. After brief introduct...
The statistical structure of dna sequences is of great interest to molecular biology, genetics and t...
Motivation: Next Generation Sequencing (NGS) technologies generate large amounts of short read data ...
Abstract—In this paper, we explore the application of information theory in DNA sequence analysis. T...
A new framework of genetic sequence statistical analysis based on generalized logit model is introdu...
This work proposes a Markovian memoryless model for the DNA that simplifies enormously the complexit...
Gene detection in DNA sequences is one of the most difficult problems, which have been currently sol...
Recently Peres and Shields discovered a new method for estimating the order of a stationary fixed or...
Methods of inference of the evolutionary history leading to currently extant species, or taxa, have ...
This thesis concerns the development of methods and models in evolutionary molecular biology. The te...
Probability models are employed in the analysis of data emerging from DNA sequence studies. To seque...
Hidden Markov models (HMM\u27s) are a specific case of Markov models where, contrary to Markov chain...
Abstract In this paper, we made a brief introduction to the recent progress of sequences analysis me...
Many of the same modeling methods used in natural languages, specifically Markov models and HMM\u27s...
S.S. and M.S.B. acknowledge the Engineering and Physical Sciences Research Council (EPSRC), grant re...
The research of Gene Predicting Algorithms is a key section in bioinformatics. After brief introduct...
The statistical structure of dna sequences is of great interest to molecular biology, genetics and t...
Motivation: Next Generation Sequencing (NGS) technologies generate large amounts of short read data ...
Abstract—In this paper, we explore the application of information theory in DNA sequence analysis. T...
A new framework of genetic sequence statistical analysis based on generalized logit model is introdu...
This work proposes a Markovian memoryless model for the DNA that simplifies enormously the complexit...
Gene detection in DNA sequences is one of the most difficult problems, which have been currently sol...
Recently Peres and Shields discovered a new method for estimating the order of a stationary fixed or...
Methods of inference of the evolutionary history leading to currently extant species, or taxa, have ...
This thesis concerns the development of methods and models in evolutionary molecular biology. The te...
Probability models are employed in the analysis of data emerging from DNA sequence studies. To seque...
Hidden Markov models (HMM\u27s) are a specific case of Markov models where, contrary to Markov chain...
Abstract In this paper, we made a brief introduction to the recent progress of sequences analysis me...
Many of the same modeling methods used in natural languages, specifically Markov models and HMM\u27s...
S.S. and M.S.B. acknowledge the Engineering and Physical Sciences Research Council (EPSRC), grant re...
The research of Gene Predicting Algorithms is a key section in bioinformatics. After brief introduct...