A metric model of amino acid substitution

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A metric model of amino acid substitution

MOTIVATION We address the question of whether there exists an effective evolutionary model of amino-acid substitution that forms a metric-distance function. There is always a trade-off between speed and sensitivity among competing computational methods of determining sequence homology. A metric model of evolution is a prerequisite for the development of an entire class of fast sequence analysis...

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Errata for “A Metric Model of Amino Acid Substitution”

Motivation: We address the question of whether there exists an effective evolutionary model of amino-acid substitution that forms a metric-distance function. There is always a trade-off between speed and sensitivity among competing computational methods of determining sequence homology. A metric model of evolution is a prerequisite for the development of an entire class of fast sequence analysi...

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Amino Acid Substitution Scores

GNPKVKAH Here we discuss standard ways of assigning a score to each amino acid pair, i.e., to each possible column of a gap-free pairwise protein alignment. Examples of such scoring matrices include the PAM30, PAM70, BLOSUM80, BLOSUM62 and BLOSUM45 matrices that are available on NCBI’s blastp server. Such scores are appropriate for comparing two sequences about which we have no other informatio...

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Amino Acid Substitution Scores

GNPKVKAH Here we discuss standard ways of assigning a score to each amino acid pair, i.e., to each possible column of a gap-free pairwise protein alignment. Examples of such scoring matrices include the PAM30, PAM70, BLOSUM80, BLOSUM62 and BLOSUM45 matrices that are available on NCBI’s blastp server. Such scores are appropriate for comparing two sequences about which we have no other informatio...

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Amino acid substitution matrices.

The BLOSUM (BLOck SUbstitution Matrices) matrices were derived by Steven and Jorja Henikoff in 1992 1. They were based on a much larger data set than the PAM matrices, and used conserved local alignments or “blocks,” rather than global alignments of very closely related sequences. In order to account for different degrees of sequence divergence, the Henikoffs used clustering rather than an expl...

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ژورنال

عنوان ژورنال: Bioinformatics

سال: 2004

ISSN: 1367-4803,1460-2059

DOI: 10.1093/bioinformatics/bth065