Noise strategies for improving local search
AAAI '94 Proceedings of the twelfth national conference on Artificial intelligence (vol. 1)
Computers and Intractability: A Guide to the Theory of NP-Completeness
Computers and Intractability: A Guide to the Theory of NP-Completeness
Biclustering of Expression Data
Proceedings of the Eighth International Conference on Intelligent Systems for Molecular Biology
Enhanced Biclustering on Expression Data
BIBE '03 Proceedings of the 3rd IEEE Symposium on BioInformatics and BioEngineering
Biclustering Algorithms for Biological Data Analysis: A Survey
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
Mean Square Residue Biclustering with Missing Data and Row Inversions
ISBRA '09 Proceedings of the 5th International Symposium on Bioinformatics Research and Applications
IEEE Transactions on Information Technology in Biomedicine - Special section on body sensor networks
Mean squared residue based biclustering algorithms
ISBRA'08 Proceedings of the 4th international conference on Bioinformatics research and applications
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A biclustering algorithm, based on a greedy technique and enriched with a local search strategy to escape poor local minima, is proposed. The algorithm starts with an initial random solution and searches for a locally optimal solution by successive transformations that improve a gain function, combining the mean squared residue, the row variance, and the size of the bicluster. Different strategies to escape local minima are introduced and compared. Experimental results on yeast and lymphoma microarray data sets show that the method is able to find significant biclusters.