Clustering by pattern similarity in large data sets
Proceedings of the 2002 ACM SIGMOD international conference on Management of data
PrefixSpan: Mining Sequential Patterns by Prefix-Projected Growth
Proceedings of the 17th International Conference on Data Engineering
Biclustering of Expression Data
Proceedings of the Eighth International Conference on Intelligent Systems for Molecular Biology
OP-Cluster: Clustering by Tendency in High Dimensional Space
ICDM '03 Proceedings of the Third IEEE International Conference on Data Mining
MaPle: A Fast Algorithm for Maximal Pattern-based Clustering
ICDM '03 Proceedings of the Third IEEE International Conference on Data Mining
A Time Series Analysis of Microarray Data
BIBE '04 Proceedings of the 4th IEEE Symposium on Bioinformatics and Bioengineering
A Fast Algorithm for Subspace Clustering by Pattern Similarity
SSDBM '04 Proceedings of the 16th International Conference on Scientific and Statistical Database Management
Subspace clustering for high dimensional data: a review
ACM SIGKDD Explorations Newsletter - Special issue on learning from imbalanced datasets
Mining coherent gene clusters from gene-sample-time microarray data
Proceedings of the tenth ACM SIGKDD international conference on Knowledge discovery and data mining
Biclustering in Gene Expression Data by Tendency
CSB '04 Proceedings of the 2004 IEEE Computational Systems Bioinformatics Conference
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
TRICLUSTER: an effective algorithm for mining coherent clusters in 3D microarray data
Proceedings of the 2005 ACM SIGMOD international conference on Management of data
Clustering short time series gene expression data
Bioinformatics
Mining Shifting-and-Scaling Co-Regulation Patterns on Gene Expression Profiles
ICDE '06 Proceedings of the 22nd International Conference on Data Engineering
Quick Hierarchical Biclustering on Microarray Gene Expression Data
BIBE '06 Proceedings of the Sixth IEEE Symposium on BionInformatics and BioEngineering
Local correlation detection with linearity enhancement in streaming data
Proceedings of the 22nd ACM international conference on Conference on information & knowledge management
CoBi: Pattern Based Co-Regulated Biclustering of Gene Expression Data
Pattern Recognition Letters
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Clustering is a popular technique for analyzing microarray datasets, with n genes and m experimental conditions. As explored by biologists, there is a real need to identify co-regulated gene clusters, which includes both positive/negative regulated gene clusters. The existing pattern-based and tendency-based clustering approaches cannot be directly applied to find such co-regulated gene clusters, because they are designed for finding positive regulated gene clusters. In this paper, in order to cluster co-regulated genes, we propose a coding scheme which allows us to cluster two genes into the same cluster if they have the same code, where two genes that have the same code can be either positive or negative regulated. Based on the coding scheme, we propose a new algorithm to find maximal subspace co-regulated gene clusters with new pruning techniques. A maximal subspace co-regulated gene cluster clusters a set of genes on a condition sequence such that the cluster is not included in any other subspace co-regulated gene clusters. We conduct extensive experimental studies. Our approach can effectively and efficiently find maximal subspace co-regulated gene clusters. In addition, our approach outperforms the existing approaches to finding positive regulated gene clusters.