A sequence similarity search algorithm based on a probabilistic interpretation of an alignment scoring system.

P Bucher; K Hofmann

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PubMed · 8877503

A sequence similarity search algorithm based on a probabilistic interpretation of an alignment scoring system.

P Bucher·K Hofmann

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Abstract

We present a probabilistic interpretation of local sequence alignment methods where the alignment scoring system (ASS) plays the role of a stochastic process defining a probability distribution over all sequence pairs. An explicit algorithms is given to compute the probability of two sequences given and ASS. Based on this definition, a modified version of the Smith-Waterman local similarity search algorithm has been devised, which assesses sequence relationships by log likelihood ratios. When tested on classical examples such as globins or G-protein-coupled receptors, the new method proved to be up to an order of magnitude more sensitive than the native Smith-Waterman algorithm.

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Algorithms Cytochrome c Group GTP-Binding Proteins Globins Models, Molecular Receptors, Cell Surface Sequence Alignment Software src Homology Domains Journal Article Research Support, Non-U.S. Gov't Review

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P Bucher, K Hofmann. 1996. A sequence similarity search algorithm based on a probabilistic interpretation of an alignment scoring system.. https://pubmed.ncbi.nlm.nih.gov/8877503/

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