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

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Curating a Large-Scale Regulatory Network by Evaluating Its Consistency with Expression Datasetse systems biology field. This kind of analysis faces three common problems: the size of the model, the uncertainty in the expression datasets, and the heterogeneity of the data. On that account, we propose a method that analyses large-scale networks with small – but reliable – expression datasets. O

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Spatial Clustering of Molecular Dynamics Trajectories in Protein Unfolding Simulationsulation may indicate which residues are essential in determining the protein structure. We present a method, inspired by a popular data mining technique called Frequent Itemset Mining, that clusters sets of amino acid residues with a synchronized trajectory during the unfolding process. The proposed

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A New Linear Initialization in SOM for Biomolecular Dataloped and new tools have been introduced. Several computational methods are based on unsupervised neural network algorithms that are widely used for multiple purposes including clustering and visualization, i.e. the Self Organizing Maps (SOM). Unfortunately, even though this method is unsupervised,

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