Publication Date:
1992-07-03
Description:
Statistical approaches help in the determination of significant configurations in protein and nucleic acid sequence data. Three recent statistical methods are discussed: (i) score-based sequence analysis that provides a means for characterizing anomalies in local sequence text and for evaluating sequence comparisons; (ii) quantile distributions of amino acid usage that reveal general compositional biases in proteins and evolutionary relations; and (iii) r-scan statistics that can be applied to the analysis of spacings of sequence markers.〈br /〉〈span class="detail_caption"〉Notes: 〈/span〉Karlin, S -- Brendel, V -- GM10452-29/GM/NIGMS NIH HHS/ -- HG00335-04/HG/NHGRI NIH HHS/ -- New York, N.Y. -- Science. 1992 Jul 3;257(5066):39-49.〈br /〉〈span class="detail_caption"〉Author address: 〈/span〉Department of Mathematics, Stanford University, CA 94305.〈br /〉〈span class="detail_caption"〉Record origin:〈/span〉 〈a href="http://www.ncbi.nlm.nih.gov/pubmed/1621093" target="_blank"〉PubMed〈/a〉
Keywords:
*Amino Acid Sequence
;
Animals
;
Bacillus subtilis/genetics
;
*Base Sequence
;
DNA/chemistry/*genetics
;
Drosophila/genetics
;
Escherichia coli/genetics
;
Humans
;
Mathematics
;
*Models, Genetic
;
*Models, Statistical
;
Proteins/chemistry/*genetics
;
Saccharomyces cerevisiae/genetics
;
Viruses/genetics
Print ISSN:
0036-8075
Electronic ISSN:
1095-9203
Topics:
Biology
,
Chemistry and Pharmacology
,
Computer Science
,
Medicine
,
Natural Sciences in General
,
Physics
