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OJBTM
Online Journal of Bioinformatics ©
Volume
12(2):274-288,
2011
Neighbour
joining microarray data clustering algorithm
B.
Rajendran1 ,Vel Murugan.k2
, Premnath .D3* ,Patric Gomez4
Department
of
Bioinformatics, Karunya University, India.
ABSTRACT
Rajendran B, Murugan V, Premnath
K, Gomez P., Neighbour
joining microarray data clustering algorithm, Online J Bioinformatics,
12(2):274-288, 2011 Gene
clustering groups
related genes into a same cluster. K-means clustering algorithm is used
for
gene expression analysis, but has drawbacks which affect the accuracy
of
clustering. Neighbour-Joining (NJ)
has been
widely used for phylogenetic
reconstruction combining
computational efficiency with reasonable accuracy: RapidNJ
is an extension of the algorithm which reduces the average clustering
time.
However, the large O (n2) space consumption of RapidNJ
is a problem when inferring phylogenies with large data sets. This work
describes a method to reduce memory requirements and enable RapidNJ
to infer large data sets. An improved heuristic
search for RapidNJ improved performance on
data sets.
Performance of RapidNJ was evaluated
against accuracy
and time on lymphoma and leukemia data sets.
Keywords---Gene
clustering,
DNA, microarray, Neighbor Joining, RapidNJ