Linear manifold clustering in high dimensional spaces by stochastic search
Pattern Recognition
A Hybrid Metaheuristic for Biclustering Based on Scatter Search and Genetic Algorithms
PRIB '09 Proceedings of the 4th IAPR International Conference on Pattern Recognition in Bioinformatics
Evolutionary metaheuristic for biclustering based on linear correlations among genes
Proceedings of the 2010 ACM Symposium on Applied Computing
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Typical gene expression clustering algorithms are restricted to a specific underlying pattern model while overlooking the possibility that other information carrying patterns may co-exist in the data. This may potentially lead to a large bias in the results. In this paper we discuss a new method that is able to cluster simultaneously various types of patterns. Our method is based on the observation that many of the patterns that are considered significant to infer gene function and regulatory mechanisms all share the geometry of linear manifolds.