Multi-objective evolutionary biclustering of gene expression data
Pattern Recognition
Computers and Operations Research
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
A Hybrid Metaheuristic for Biclustering Based on Scatter Search and Genetic Algorithms
PRIB '09 Proceedings of the 4th IAPR International Conference on Pattern Recognition in Bioinformatics
IEEE Transactions on Information Technology in Biomedicine - Special section on body sensor networks
Evolutionary metaheuristic for biclustering based on linear correlations among genes
Proceedings of the 2010 ACM Symposium on Applied Computing
Biclusters evaluation based on shifting and scaling patterns
IDEAL'07 Proceedings of the 8th international conference on Intelligent data engineering and automated learning
Data analysis and bioinformatics
PReMI'07 Proceedings of the 2nd international conference on Pattern recognition and machine intelligence
Microarray data biclustering with multi-objective immune algorithm
ICNC'09 Proceedings of the 5th international conference on Natural computation
A novel probabilistic encoding for EAs applied to biclustering of microarray data
Proceedings of the 13th annual conference on Genetic and evolutionary computation
Algorithm for low-variance biclusters to identify coregulation modules in sequencing datasets
Proceedings of the Tenth International Workshop on Data Mining in Bioinformatics
Possibilistic approach to biclustering: an application to oligonucleotide microarray data analysis
CMSB'06 Proceedings of the 2006 international conference on Computational Methods in Systems Biology
Shifting patterns discovery in microarrays with evolutionary algorithms
KES'06 Proceedings of the 10th international conference on Knowledge-Based Intelligent Information and Engineering Systems - Volume Part II
Correlation–based scatter search for discovering biclusters from gene expression data
EvoBIO'10 Proceedings of the 8th European conference on Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics
A Discrete Artificial Bees Colony Inspired Biclustering Algorithm
International Journal of Swarm Intelligence Research
A new measure for gene expression biclustering based on non-parametric correlation
Computer Methods and Programs in Biomedicine
Mining low-variance biclusters to discover coregulation modules in sequencing datasets
Scientific Programming - Biological Knowledge Discovery and Data Mining
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In a gene expression data matrix a bicluster is a grouping of a subset of genes and a subset of conditions which show correlating levels of expression activity. The difficulty of finding significant biclusters in gene expression data grows exponentially with the size of the dataset and heuristic approaches such as Cheng and Churchýs greedy node deletion algorithm are required. It is to be expected that stochastic search techniques such as Genetic Algorithms or Simulated Annealing might produce better solutions than greedy search. In this paper we show that a Simulated Annealing approach 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.