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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, Onl J Bioinform., 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
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