Titlebook: Computational Intelligence Methods for Bioinformatics and Biostatistics; 6th International Me Francesco Masulli,Leif E. Peterson,Roberto Ta

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Multiple Clustering Solutions Analysis through Least-Squares Consensus Algorithmsr, different clustering algorithms applied to the same data-set produce different solutions. In many applications the problem of multiple solutions becomes crucial and providing a limited group of good clusterings is often more desirable than a single solution. In this work we propose the Least Squa

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Projection Based Clustering of Gene Expression Dataless, the tremendous amount of data that can be obtained from microarray studies presents a challenge for data analysis, mainly due to the very high data dimensionality. A particular class of clustering algorithms has been very successful in dealing with such data, utilising information driven by th

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Searching a Multivariate Partition Space Using MAX-SATe highest scoring (MAP) partition is usually impossible. Therefore, both deterministic or random search algorithms traverse only a small proportion of partitions of a large dataset. The main contribution of this paper is to encode the formal Bayes factor search on partitions as a weighted MAX-SAT pr

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Computational Intelligence Methods for Bioinformatics and Biostatistics978-3-642-14571-1Series ISSN 0302-9743 Series E-ISSN 1611-3349

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Francesco Masulli,Leif E. Peterson,Roberto TagliafUnique visibility, state-of-the-art survey,.fast-track conference proceedings

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