Titlebook: Computational Intelligence Methods for Bioinformatics and Biostatistics; 5th International Me Francesco Masulli,Roberto Tagliaferri,Gennady

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Stability and Performances in Biclustering Algorithmsbiclustering problem. This paper presents work done in this direction, by selecting some representative stability indexes and experimentally verifying and comparing their properties. Experimental results are presented that indicate both a general agreement and some differences among the selected methods.

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Clustering Bacteria Species Using Neural Gas: Preliminary Studyts a stable part of bacteria genome. The dataset used for the experiments is obtained from the Ribosomal Database Project II, and it is made of 5159 sequences of 16S rRNA genes. Preliminary results of the experiments show a promising ability of the proposed algorithm to recognize clusters of the actual bacteria taxonomy.

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Conference proceedings 2009from different disciplines to present and discuss problems concerning computational techniques in bioinformatics, systems biology and medical informatics with a particular focus on neural networks, machine learning, fuzzy logic, and evolutionary computation methods.

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https://doi.org/10.1007/978-3-322-80249-1s. Experimental results show that GenMiner requires less memory than Apriori based approaches and that it improves the relevance of extracted rules. Moreover, association rules obtained revealed significant co-annotated and co-expressed gene patterns showing important biological relationships supported by recent biological literature.

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,Mehrstufige stochastische Vorg?nge,l plant Arabidopsis thaliana. The performance is then measured using a completely distinct gene set of 5000 genes, and verified at a set of 20 genes. The best measured performance on the verification data set of 20 genes, gives a sensitivity of 0.891, a specificity of 0.816 and a correlation coefficient of 0.552.

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