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)
A Time-Series Biclustering Algorithm for Revealing Co-Regulated Genes
ITCC '05 Proceedings of the International Conference on Information Technology: Coding and Computing (ITCC'05) - Volume I - Volume 01
Multi-objective evolutionary biclustering of gene expression data
Pattern Recognition
Guest Editorial: Special Issue on Bioinformatics
Pattern Recognition
A linear time biclustering algorithm for time series gene expression data
WABI'05 Proceedings of the 5th International conference on Algorithms in Bioinformatics
Genetic programming for anticancer therapeutic response prediction using the NCI-60 dataset
Computers and Operations Research
Aggregation of correlation measures for the reverse engineering of gene regulatory sub-networks
PerMIn'12 Proceedings of the First Indo-Japan conference on Perception and Machine Intelligence
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In this study, a novel rank correlation-based multiobjective evolutionary biclustering method is proposed to extract simple gene interaction networks from microarray data. Preprocessing helps to preserve those gene interaction pairs which are strongly correlated. Experimental results on time series gene expression data from Yeast are biologically validated based on standard databases and information from literature.