Application of simulated annealing to the biclustering of gene expression data
Citation:
Bryan K., Cunningham P., Bolshakova N. `Application of simulated annealing to the biclustering of gene expression data? in IEEE Transactions on Information Technology on Biomedicine, 10, (3), 2006, pp 519-525Download Item:
Abstract:
In a gene expression data matrix, a bicluster is a submatrix
of genes and conditions that exhibits a high correlation of
expression activity across both rows and columns. The problem
of locating the most significant bicluster has been shown to be
NP-complete. Heuristic approaches such as Cheng and Church?s
greedy node deletion algorithm have been previously employed.
It is to be expected that stochastic search techniques such as evolutionary
algorithms or simulated annealing might improve upon
such greedy techniques. In this paper we show that an approach
based on simulated annealing is well suited to this problem, and we
present a comparative evaluation of simulated annealing and node
deletion on a variety of datasets.We show that simulated annealing
discovers more significant biclusters in many cases. Furthermore,
we also test the ability of our technique to locate biologically verifiable
biclusters within an annotated set of genes.
Sponsor
Grant Number
Science Foundation Ireland
Author's Homepage:
http://people.tcd.ie/bolshaknDescription:
PUBLISHED
Author: BOLSHAKOVA, NADIA; CUNNINGHAM, PADRAIG
Type of material:
Journal ArticleCollections
Series/Report no:
IEEE Transactions on Information Technology on Biomedicine10
3
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Full text availableKeywords:
biclustering, data mining, gene expression, simulated annealingMetadata
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