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

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摘要記錄

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Bayesian Models for the Multi-sample Time-Course Microarray Experimentsompromise 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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Reliability of miRNA Microarray Platforms: An Approach Based on Random Effects Linear Models in terms of within-sample repeatability and between-lines reproducibility. Validation on publicly available NCI60 dataset showed similar patterns of variability, suggesting good reproducibility between experiments..Future research will explore the possibility to use this method to compare normalization methods as well as genomic platforms.

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Integration of Biomolecular Interaction Data in a Genomic and Proteomic Data Warehouse to Support Biata in the GPDW. The comprehensive and mining of the reliable interaction data together with the other biomolecular information in the GPDW constitutes a powerful computational support for novel biomedical knowledge discoveries.

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Biostatistics Meets Bioinformatics in Integrating Information from Highdimensional Heterogeneous Gen of datasets from Gene Therapy and Tubercolosis to highlight how integration between biostatistics and bioinformatics allows to gain information from the extremely large biogical databases produced with the new biotechnologies, such as Next Generation Sequencing (NGS) data.

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