title: Geometric approach to string analysis for biosequence classification.
abstract: Tools that effectively analyze and compare sequences are of great importance in various areas of applied computational research, especially in the framework of molecular biology. In the present paper, we introduce simple geometric criteria based on the notion of string linearity and use them to compare DNA sequences of various organisms, as well as to distinguish them from random sequences. Several other theoretical and statistical results are outlined as well. Our experiments reveal a substantial difference between biosequences and random sequences &ndash; the former having much higher deviation from linearity than the latter &ndash; as well as a general trend of increasing deviation from linearity between primitive and biologically complex organisms.
authors.affiliation: Computational and Applied Mathematics, Rice University, Houston, TX 77005, USA.
authors.forename: Boris
authors.initials: B
authors.lastname: Brimkov
mesh_terms: D000465:Algorithms; D000818:Animals; D001483:Base Sequence; D019295:Computational Biology / Q000379:methods*; D006801:Humans; D016415:Sequence Alignment