@inproceedings{f43022ecbfc94b23b92fbf449454ad68,
title = "Possibilistic approach to biclustering: An application to oligonucleotide microarray data analysis",
abstract = "The important research objective of identifying genes with similar behavior with respect to different conditions has recently been tackled with biclustering techniques. In this paper we introduce a new approach to the biclustering problem using the Possibilistic Clustering paradigm. The proposed Possibilistic Biclustering algorithm finds one bicluster at a time, assigning a membership to the bicluster for each gene and for each condition. The biclustering problem, in which one would maximize the size of the bicluster and minimizing the residual, is faced as the optimization of a proper functional. We applied the algorithm to the Yeast database, obtaining fast convergence and good quality solutions. We discuss the effects of parameter tuning and the sensitivity of the method to parameter values. Comparisons with other methods from the literature are also presented.",
author = "Maurizio Filippone and Francesco Masulli and Stefano Rovetta and Sushmita Mitra and Haider Banka",
year = "2006",
doi = "10.1007/11885191_22",
language = "English (US)",
isbn = "3540461663",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "312--322",
booktitle = "Computational Methods in Systems Biology - International Conference, CMSB 2006, Proceedings",
address = "Germany",
note = "International Conference on Computational Methods in Systems Biology, CMSB 2006 ; Conference date: 18-10-2006 Through 19-10-2006",
}