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Science 3 July 1992:
Vol. 257. no. 5066, pp. 39 - 49
DOI: 10.1126/science.1621093
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Articles
Science, Vol 257, Issue 5066, 39-49
Copyright © 1992 by American Association for the Advancement of Science
Chance and statistical significance in protein and DNA sequence analysis
S Karlin
and
V Brendel
Department of Mathematics, Stanford University, CA 94305.
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.
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