Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Multi-Objective Optimization Using Evolutionary Algorithms
Multi-Objective Optimization Using Evolutionary Algorithms
Discovering local structure in gene expression data: the order-preserving submatrix problem
Proceedings of the sixth annual international conference on Computational biology
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
Data Mining: Concepts and Algorithms From Multimedia to Bioinformatics
Data Mining: Concepts and Algorithms From Multimedia to Bioinformatics
The maximum edge biclique problem is NP-complete
Discrete Applied Mathematics
Microarray data mining: facing the challenges
ACM SIGKDD Explorations Newsletter
Mining Deterministic Biclusters in Gene Expression Data
BIBE '04 Proceedings of the 4th IEEE Symposium on Bioinformatics and Bioengineering
Subspace clustering for high dimensional data: a review
ACM SIGKDD Explorations Newsletter - Special issue on learning from imbalanced datasets
Biclustering in Gene Expression Data by Tendency
CSB '04 Proceedings of the 2004 IEEE Computational Systems Bioinformatics Conference
Gene Ontology Friendly Biclustering of Expression Profiles
CSB '04 Proceedings of the 2004 IEEE Computational Systems Bioinformatics Conference
Biclustering Algorithms for Biological Data Analysis: A Survey
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
Cluster Analysis for Gene Expression Data: A Survey
IEEE Transactions on Knowledge and Data Engineering
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
Attribute Clustering for Grouping, Selection, and Classification of Gene Expression Data
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
Biclustering of Expression Data Using Simulated Annealing
CBMS '05 Proceedings of the 18th IEEE Symposium on Computer-Based Medical Systems
Biclustering Models for Structured Microarray Data
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
Biclustering of Expression Data with Evolutionary Computation
IEEE Transactions on Knowledge and Data Engineering
Discovering significant OPSM subspace clusters in massive gene expression data
Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining
A linear time biclustering algorithm for time series gene expression data
WABI'05 Proceedings of the 5th International conference on Algorithms in Bioinformatics
Order preserving clustering over multiple time course experiments
EC'05 Proceedings of the 3rd European conference on Applications of Evolutionary Computing
Evolutionary Rough Feature Selection in Gene Expression Data
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
A fast and elitist multiobjective genetic algorithm: NSGA-II
IEEE Transactions on Evolutionary Computation
A Discrete Artificial Bees Colony Inspired Biclustering Algorithm
International Journal of Swarm Intelligence Research
CoBi: Pattern Based Co-Regulated Biclustering of Gene Expression Data
Pattern Recognition Letters
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With the advent of microarray technology it has been possible to measure thousands of expression values of genes in a single experiment. Biclustering or simultaneous clustering of both genes and conditions is challenging particularly for the analysis of high-dimensional gene expression data in information retrieval, knowledge discovery, and data mining. The objective here is to find sub-matrices, i.e., maximal subgroups of genes and subgroups of conditions where the genes exhibit highly correlated activities over a range of conditions while maximizing the volume simultaneously. Since these two objectives are mutually conflicting, they become suitable candidates for multi-objective modeling. In this study, we will describe some recent literature on biclustering as well as a multi-objective evolutionary biclustering framework for gene expression data along with the experimental results.