title: Statistical analysis of nucleotide sequences.
abstract: In order to scan nucleic acid databases for potentially relevant but as yet unknown signals, we have developed an improved statistical model for pattern analysis of nucleic acid sequences by modifying previous methods based on Markov chains. We demonstrate the importance of selecting the appropriate parameters in order for the method to function at all. The model allows the simultaneous analysis of several short sequences with unequal base frequencies and Markov order k not equal to 0 as is usually the case in databases. As a test of these modifications, we show that in E. coli sequences there is a bias against palindromic hexamers which correspond to known restriction enzyme recognition sites.
authors: Max-Planck-Institut für Immunbiologie, Freiburg, FRG.
authors: E E
authors: EE
authors: Stückle
authors: C
authors: C
authors: Emmrich
authors: U
authors: U
authors: Grob
authors: P J
authors: PJ
authors: Nielsen
mesh_terms: D001483:Base Sequence; D016208:Databases, Factual; D015233:Models, Statistical; D008969:Molecular Sequence Data; D010363:Pattern Recognition, Automated; D012091:Repetitive Sequences, Nucleic Acid