Biclustering of Expression Data
Proceedings of the Eighth International Conference on Intelligent Systems for Molecular Biology
Biclustering Algorithms for Biological Data Analysis: A Survey
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
Decision rule-based data models using TRS and NetTRS – methods and algorithms
Transactions on Rough Sets XI
A refactoring method for cache-efficient swarm intelligence algorithms
Information Sciences: an International Journal
Foundations of rough biclustering
ICAISC'12 Proceedings of the 11th international conference on Artificial Intelligence and Soft Computing - Volume Part II
eBi --- the algorithm for exact biclustering
ICAISC'12 Proceedings of the 11th international conference on Artificial Intelligence and Soft Computing - Volume Part II
Hi-index | 0.00 |
This paper presents a new approach for the biclustering problem. For this purpose new notions like half-bicluster and biclustering matrix were developed. Results obtained with the algorithm BicDM (Biclustering of Discrete value Matrix) were compared with some other methods of biclustering. In this article the new algorithm is applied for binary data but there is no limitation to use it for other discrete type data sets. In this paper also two postprocessing steps are defined: generalization and filtering. In the first step biclusters are generalized and after that only those which are the best become the final set - weak biclusters are filtered from the set. The usage of the algorithm makes it possible to improve the description of data with the reduction of bicluster number without the loss of information. The postprocessing was performed on the new algorithm results and compared with other biclustering methods.