176178
20180913061219.0
1553-0833
ARTICLE
A sequence similarity search algorithm based on a probabilistic interpretation of an alignment scoring system
1996
1996
Reviews
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.
Algorithms
Models, Molecular
Bucher, P.
113607
244404
Hofmann, K.
44-51
Proceedings / ... International Conference on Intelligent Systems for Molecular Biology ; ISMB. International Conference on Intelligent Systems for Molecular Biology
4
GR-BUCHER
252244
U11780
oai:infoscience.tind.io:176178
review
SV
182396
EPFL-REVIEW-176178
OTHER
PUBLISHED
REVIEWED
REVIEW