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PMID: 1480466 Published · ppublish English Journal Article Research Support, Non-U.S. Gov't Research Support, U.S. Gov't, Non-P.H.S. Research Support, U.S. Gov't, P.H.S. Review

Assessment of protein coding measures.

Nucleic acids research ·Vol. 20 ·No. 24 ·1992-12-25 ·Pages 6441-50

Fickett JW, Tung CS

Abstract

A number of methods for recognizing protein coding genes in DNA sequence have been published over the last 13 years, and new, more comprehensive algorithms, drawing on the repertoire of existing techniques, continue to be developed. To optimize continued development, it is valuable to systematically review and evaluate published techniques. At the core of most gene recognition algorithms is one or more coding measures--functions which produce, given any sample window of sequence, a number or vector intended to measure the degree to which a sample sequence resembles a window of 'typical' exonic DNA. In this paper we review and synthesize the underlying coding measures from published algorithms. A standardized benchmark is described, and each of the measures is evaluated according to this benchmark. Our main conclusion is that a very simple and obvious measure--counting oligomers--is more effective than any of the more sophisticated measures. Different measures contain different information. However there is a great deal of redundancy in the current suite of measures. We show that in future development of gene recognition algorithms, attention can probably be limited to six of the twenty or so measures proposed to date.

MeSH Terms
Algorithms Base Composition Base Sequence Codon/genetics DNA/genetics Exons Fourier Analysis Genes Genetic Techniques Humans Proteins/genetics
Chemicals
Codon Proteins DNA
Authors & Affiliations
2 authors, click to expand affiliations / ORCID
Fickett J W
Theoretical Biology and Biophysics Group, Los Alamos National Laboratory, NM 87545.
Tung C S
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Article Info
Journal
Nucleic acids research
Abbr.
Nucleic Acids Res
ISSN
0305-1048
DOI
10.1093/nar/20.24.6441
Published
1992-12-25
Pages
6441-50
Language
English
Region
England
NLM ID
0411011
PMCID
PMC334555
Subset
IM
Grants
NIGMS NIH HHS · GM-37812 · United States
External Links
PubMed source DOI: 10.1093/nar/20.24.6441 PMC Full Text View journal details
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