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Titlebook: Computational Intelligence Methods for Bioinformatics and Biostatistics; 8th International Me Elia Biganzoli,Alfredo Vellido,Roberto Taglia

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Conference proceedings 2012 carefully reviewed and selected from 24 submissions. The papers are organized in topical sections on statistical learning, genomics, computational intelligence for health at the edge, proteomics, intelligent clinical decision support systems (i-CDSS), bioinformatics, and data clustering.
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Norbert Henze,Kai Müller,Judith Schillingy groups of genes whose interactions are modified by an underlying condition. The proposal is independent from the classification algorithm used. Two applications on genomewide data are presented regarding children susceptibility to air pollution and early and late onset of Parkinson’s disease.
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Norbert Henze,Kai Müller,Judith Schilling blind source separation to map the pathways of biomarkers driving independent, hidden processes that underpin the clusters. The method is applied to a protein expression data set measured in tissue from breast cancer patients (.=1,076).
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Wolfgang Hackenbroch,Anton Thalmaieraper, for first time, we combine these elements and we present ISPRED2, a new HM-SVM-based method that overpasses the state of the art performance (Q2=0.71 and correlation=0.43). ISPRED2 consists of a sets of Python scripts aimed at integrating the different third-party software to obtain the final prediction.
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https://doi.org/10.1007/978-3-658-33779-7ompromise between nonparametric and normality assumption based techniques. In addition, all evaluations are carried out using analytic expressions, hence, the entire procedure requires very small computational effort. The performance of the procedure is studied using simulated data.
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