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image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Bulletin of Mathemat...arrow_drop_down
image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
Bulletin of Mathematical Biology
Article . 1992 . Peer-reviewed
License: Springer TDM
Data sources: Crossref
image/svg+xml Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao Closed Access logo, derived from PLoS Open Access logo. This version with transparent background. http://commons.wikimedia.org/wiki/File:Closed_Access_logo_transparent.svg Jakob Voss, based on art designer at PLoS, modified by Wikipedia users Nina and Beao
zbMATH Open
Article . 1992
Data sources: zbMATH Open
Bulletin of Mathematical Biology
Article . 1992 . Peer-reviewed
Data sources: Crossref
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Poisson, compound poisson and process approximations for testing statistical significance in sequence comparisons

Poisson, compound Poisson and process approximations for testing statistical significance in sequence comparisons
Authors: Goldstein, Larry; Waterman, Michael S.;

Poisson, compound poisson and process approximations for testing statistical significance in sequence comparisons

Abstract

DNA and protein sequence comparisons are performed by a number of computational algorithms. Most of these algorithms search for the alignment of two sequences that optimizes some alignment score. It is an important problem to assess the statistical significance of a given score. In this paper we use newly developed methods for Poisson approximation to derive estimates of the statistical significance of k-word matches on a diagonal of a sequence comparison. We require at least q of the k letters of the words to match where 0 less than q less than or equal to k. The distribution of the number of matches on a diagonal is approximated as well as the distribution of the order statistics of the sizes of clumps of matches on the diagonal. These methods provide an easily computed approximation of the distribution of the longest exact matching word between sequences. The methods are validated using comparisons of vertebrate and E. coli protein sequences. In addition, we compare two HLA class II transplantation antigens by this method and contrast the results with a dynamic programming approach. Several open problems are outlined in the last section.

Related Organizations
Keywords

compound Poisson, null hypothesis of sequence independence, Molecular Sequence Data, Applications of statistics to biology and medical sciences; meta analysis, approximate distributions, Animals, Amino Acid Sequence, Poisson Distribution, Computational methods for problems pertaining to biology, extreme value distribution, word matches, Proteins, Protein sequences, DNA sequences, longest exact matching word, Data Interpretation, Statistical, distribution of order statistics, protein sequence comparisons, significance tests, Poisson approximation, dynamic programming approach, Sequence Alignment, DNA sequence comparisons, Algorithms, Mathematics

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
29
Average
Top 10%
Average
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