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OJBTM
Online Journal of Bioinformatics ©
Volume
12(1):74-84, 2011
Self organizing
genetic algorithms for local and
global multiple sequence alignment
Amouda V1*, Buvaneswari
S1, Kuppuswami
S2
1Centre
for Bioinformatics, 2Department
of Computer Science R.V. Nagar, Kalapet, Pondicherry
University, Puducherry- 605 014
ABSTRACT
Amouda V, Buvaneswari S, Kuppuswami
S, Self organizing genetic algorithms for local and global multiple sequence alignment, Online J
Bioinformatics, 12(1): 74-84, 2011. A global multiple sequence alignment algorithm (SOGA)
includes 2 new operators which perform a self organizing crossover and mutation
operation for the required number of generations. Another algorithm (SOSW)
performs pairwise alignment and progressively aligns
it to a local multiple sequence alignment (MSA) based on the alignment score.
Many MSA tools and genetic alignment algorithms have parameter values either as
default or optional making it difficult to select appropriate method and
parameter values since the sequence is unknown. The proposed algorithms select
appropriate alignment and parameter values based on sequence length, identity and
alignment score, reducing time to optimize parameter values and prevent
execution with default values. A score columm then compares
alignment to validate results.
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