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A perturbation-based method for calculating explicit likelihood of evolutionary co-variance in multiple sequence alignments
Author(s) -
John P. Dekker,
Anthony A. Fodor,
Richard W. Aldrich,
Gary Yellen
Publication year - 2004
Publication title -
bioinformatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.599
H-Index - 390
eISSN - 1367-4811
pISSN - 1367-4803
DOI - 10.1093/bioinformatics/bth128
Subject(s) - variance (accounting) , sequence (biology) , perturbation (astronomy) , computer science , algorithm , mathematics , computational biology , biology , genetics , physics , accounting , business , quantum mechanics
The constituent amino acids of a protein work together to define its structure and to facilitate its function. Their interdependence should be apparent in the evolutionary record of each protein family: positions in the sequence of a protein family that are intimately associated in space or in function should co-vary in evolution. A recent approach by Ranganathan and colleagues proposes to look at subsets of a protein family, selected for their sequence at one position, to see how this affects variation at other positions.

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