at
http://cnd.memphis.edu/ijcnn2009/
[1] Y. Cheng and G. M. Church, Biclustering of
expression data. Proc Int Conf Intell Syst Mol Biol, vol. 8, pp.
93-103, 2000.
[2] S. C. Madeira and A. L. Oliveira, Biclustering algorithms for
biological data analysis: A survey, IEEE Transactions on Computational
Biology and Bioinformatics, vol. 1, pp. 24-45, 2004.
[3] K. Umayahara, S. Miyamoto, and Y. Nakamori, Formulations of
fuzzy
clustering for categorical data, Int. J. of Innovative Computing,
Information and Control, vol. 1, no. 1, pp. 83-94, 2005.
[4] W.-C. Tjhi and L. Chen, Minimum sum-squared residue for fuzzy
co-clustering, Intelligent Data Analysis, vol. 10, no. 3, pp. 237-249,
2006.
[5] C. Cano, L. Adarve, J. Lopez, and A. Blanco, Possibilistic
approach for biclustering microarray data, Computers in Biology and
Medicine, vol. 37, no. 10, pp. 1426-1436, October 2007.
[6] M. Filippone, F. Masulli, S. Rovetta, S. Mitra, and H. Banka,
Possibilistic approach to biclustering: An application to
oligonucleotide microarray data analysis.in Lecture Notes in
Bioinformatics, C. Priami, Ed., vol. 4210. Springer, October 2006, pp.
312-322.
[7] J. Yang, H. Wang, W. Wang, and P. Yu, Enhanced biclustering
on
expression data, in BIBE 03: Proceedings of the 3rd IEEE Symposium on
BioInformatics and BioEngineering. Washington, DC, USA: IEEE Computer
Society, 2003, p. 321.
[8] M. Filippone, F. Masulli, and S. Rovetta, Comparing Fuzzy
Approaches to Biclustering, Computational
Intelligence Methods for Bioinformatics and Biostatistics, Proceedings
of the CIBB 2008,
LNCS/LNBI,
Springer-Verlag, Heidelberg (Germany), 2008 (in press).
Francesco Masulli (1,2) and Stefano Rovetta (1)
(1) DISI
Dept. Computer and Information Sciences
University of Genova and CNISM
Via Dodecaneso 35, 16146 Genoa, Italy
E-mails: masulli <at> disi.unige.it, rovetta <at>
disi.unige.it
(3)
Sbarro Institute for Cancer Research and Molecular Medicine,
Temple University, 1900 N 12th Street Philadelphia, PA 19122, USA