Statistical analysis of nucleotide sequences.

Nucleic acids research ·Vol. 18 ·No. 22 ·1990-11-25 ·Pages 6641-7

Stückle EE, Emmrich C, Grob U, Nielsen PJ

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.

MeSH Terms

Base Sequence Databases, Factual Models, Statistical Molecular Sequence Data Pattern Recognition, Automated Repetitive Sequences, Nucleic Acid

Authors & Affiliations

4 authors, click to expand affiliations / ORCID

Stückle E E

Max-Planck-Institut für Immunbiologie, Freiburg, FRG.

Emmrich C

Grob U

Nielsen P J

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Article Info

Journal

Nucleic acids research

Abbr.

Nucleic Acids Res

ISSN

0305-1048

DOI

10.1093/nar/18.22.6641

Published

1990-11-25

Pages

6641-7

Language

English

Region

England

NLM ID

0411011

PMCID

PMC332623

Subset

External Links

PubMed source DOI: 10.1093/nar/18.22.6641 PMC Full Text View journal details

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