For DNA sequences of various species we construct the Google matrix G 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 G 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.Comment: latex, 11 fig