Titlebook: Computational Intelligence Methods for Bioinformatics and Biostatistics; 14th International M Massimo Bartoletti,Annalisa Barla,Roberto Tag

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Determinants of Stock Market Integration,energy statistics, which is a class of statistics based on distances. Subsequently, our method assigns a measure of statistical significance to each candidate modulator through a permutation test. We compared our approach with that of a leading competitor for identifying modulators, and illustrated

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Stock Market Modeling and Forecastingaccount if one intends to adsorb intact lipid structures. Liposome flattening is observed and justified by the attractive electrostatic interactions occurring between the negatively charged lipid liposomes and the outermost, positively charged polyelectrolyte layer of the cushion. The conducted meas

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Extracting Few Representative Reconciliations with Host Switches,a phylogenetic tree for each such set, respectively denoted by . and ., together with a mapping . of the leaves of . to the leaves of ., a reconciliation is a mapping . of the internal vertices of . to the vertices of . which extends . with some constraints..Given a cost for each reconciliation, a h

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A Quantitative and Qualitative Characterization of ,-mer Based Alignment-Free Phylogeny Constructioganisms, and challenges standard techniques that require multiple sequence alignment. Further, the ability to probe variations in selection pressure e.g. among viral outbreaks, is an important characterization of the life of a virus in its biological reservoir..In this paper, we derived the probabil

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Cancer Mutational Signatures Identification with Sparse Dictionary Learning,ic mutations have been studied in order to understand which processes or conditions may generate them, with the purpose of developing prevention and treatment strategies. In this work we propose a novel sparse regularised method that aims at extracting mutational signatures from somatic mutations. W

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: A HPC-Oriented Tool for Biological Data Exploration,nd quick overview of the main structures underlying their data. This software tool encompasses state-of-the-art techniques for missing values imputing, data preprocessing, dimensionality reduction and clustering. . has a scalable architecture which seamlessly work on single workstations as well as o

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,Disease–Genes Must Guide Data Source Integration in the Gene Prioritization Process,nctional relationships between genes. Numerous approaches exploited the complementary evidence coded in heterogeneous sources of data to prioritize disease-genes, such as functional profiles or expression quantitative trait loci, but none of them to our knowledge posed the scarcity of known disease-

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Ensembling Descendant Term Classifiers to Improve Gene - Abnormal Phenotype Predictions,relationship between them. Quite surprisingly the problem of the automated prediction of the association between genes and abnormal human phenotypes has been widely overlooked, even if this issue represents an important step toward the characterization of gene-disease associations, especially when n