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DNA sequences are often found to be composed of locally homogeneous segments that are functionally important. Most sequence comparison methods do not consider such a compositional property. We introduce a new method that takes this issue into consideration. With our method, the information of a DNA sequence is first transformed into a multi-order transition matrix (MTM); the resulting matrices are...
We consider DNA codes based on the nearest-neighbor (stem) similarity model which adequately reflects the “hybridization potential” of two DNA sequences. Our aim is to present a survey of bounds on the rate of DNA codes with respect to a thermodynamically motivated similarity measure called an additive stem similarity. These results yield a method to analyze and compare known samples of the nearest...
The statistical structure of DNA-sequences is of a great interest to molecular biology, genetics and theory of evolution. One of the approaches is sequence modeling using Markov processes of different orders, and further statistical estimation of their parameters. This approach is evolved in the paper and the test for serial independence, suggested by Ryabko, Astola (Stat.Methodology, 2006), is used...
Fixation of advantageous mutations is an important evolutionary force driving the accelerated protein diversification. However, the standard phylogenetic approach to infer positive selection is based on relative rate of nonsynonymous to synonymous substitutions, and requires the knowledge of DNA sequences, hence precludes its application to family of remotely related sequences where saturated substitution...
This paper proposes a novel algorithm for inferring genetic regulatory networks by exploiting the knowledge of gene expressions, DNA sequences and binding sites. The integration of multiple data sources helps to improve both the specificity and the sensitivity of network inference. The transcription factors of a target gene are determined by applying the reversible jump Markov chain Monte-Carlo (RJMCMC)...
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