Multilevel k-way hypergraph partitioning
Proceedings of the 36th annual ACM/IEEE Design Automation Conference
Biclustering of Expression Data
Proceedings of the Eighth International Conference on Intelligent Systems for Molecular Biology
Information-theoretic co-clustering
Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining
Biclustering Algorithms for Biological Data Analysis: A Survey
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
Multi-objective evolutionary biclustering of gene expression data
Pattern Recognition
Bicluster Algorithm and Used in Market Analysis
WKDD '09 Proceedings of the 2009 Second International Workshop on Knowledge Discovery and Data Mining
Gene interaction - An evolutionary biclustering approach
Information Fusion
Clustering categorical data using an extended modularity measure
ICONIP'10 Proceedings of the 17th international conference on Neural information processing: models and applications - Volume Part II
Neurocomputing
GPU-Based biclustering for neural information processing
ICONIP'12 Proceedings of the 19th international conference on Neural Information Processing - Volume Part V
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Biclustering is one of the important techniques in neurocomputing and bioinformatics. Geometric Biclustering (GBC) algorithm is used to find the common patterns in given microarray data for neural processing. A microarray can produce a massive amount of data and require high computational power for data analysis. With intrinsic parallel architecture and appropriate mapping technique Graphical Processing Unit (GPU) has the advantage of processing large number of threads and data compared to CPU. This paper analyzes the parallelism and data reuse of the GBC algorithm, and presents three different efficient implementations using five benchmarks from real world. The proposed GPU-based GBC program achieves significant speedup over highly optimized CPU program. By comparing implementation results, the paper studies how to design a scalable architecture for mapping the GBC and other similar algorithms that deal with microarray data analysis. The paper also explores how GPU-based GBC is affected by the input data size.