ArticlePloS one2013
Google matrix analysis of DNA sequences.
Article in PloS one, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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3 citing papers in PubMed.
- A Stochastic Phylogenetic Algorithm for Mitochondrial DNA Analysis.Frontiers in genetics · 2019Article
- Interactions of cultures and top people of Wikipedia from ranking of 24 language editions.PloS one · 2015Article
- Highlighting entanglement of cultures via ranking of multilingual Wikipedia articles.PloS one · 2013Article
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2 authors.
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Abstract
For DNA sequences of various species we construct the Google matrix [Formula: see text] of Markov transitions between nearby words composed of several letters. The statistical distribution of matrix elements of this matrix is shown to be described by a power law with the exponent being close to those of outgoing links in such scale-free networks as the World Wide Web (WWW). At the same time the sum of ingoing matrix elements is characterized by the exponent being significantly larger than those typical for WWW networks. This results in a slow algebraic decay of the PageRank probability determined by the distribution of ingoing elements. The spectrum of [Formula: see text] is characterized by a large gap leading to a rapid relaxation process on the DNA sequence networks. We introduce the PageRank proximity correlator between different species which determines their statistical similarity from the view point of Markov chains. The properties of other eigenstates of the Google matrix are also discussed. Our results establish scale-free features of DNA sequence networks showing their similarities and distinctions with the WWW and linguistic networks.
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