Nucleic Acids Research, Vol 24, Issue 8 1515-1524, Copyright © 1996 by Oxford University Press
C Notredame and DG Higgins
We describe a new approach to multiple sequence alignment using genetic
algorithms and an associated software package called SAGA. The method
involves evolving a population of alignments in a quasi evolutionary manner
and gradually improving the fitness of the population as measured by an
objective function which measures multiple alignment quality. SAGA uses an
automatic scheduling scheme to control the usage of 22 different operators
for combining alignments or mutating them between generations. When used to
optimise the well known sums of pairs objective function, SAGA performs
better than some of the widely used alternative packages. This is seen with
respect to the ability to achieve an optimal solution and with regard to
the accuracy of alignment by comparison with reference alignments based on
sequences of known tertiary structure. The general attraction of the
approach is the ability to optimise any objective function that one can
invent.
ARTICLES
SAGA: sequence alignment by genetic algorithm
EMBL outstation, The European Bioinformatics Institute, Cambridge, UK.
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