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  • Selected papers from the 15...
    Cazzaniga, Paolo; Raposo, Maria; Besozzi, Daniela; Merelli, Ivan; Staiano, Antonino; Ciaramella, Angelo; Rizzo, Riccardo; Manzoni, Luca

    BMC bioinformatics, 04/2021, Letnik: 22, Številka: Suppl 2
    Journal Article

    CIBB is a venue that embraces researchers with different backgrounds, ranging from mathematics to computer science, from materials science to medicine, and from engineering to biology, all interested in the investigation and application of computational intelligence methods to open problems in bioinformatics, biostatistics, systems biology, synthetic biology, and medical informatics. The program of this edition was organized with contributions on the main conference scientific area with heterogeneous open problems at the forefront of current research, and in special sessions on specific themes as Computational Methods for Neuroimaging Analysis, Machine Learning in Health Informatics and Biological Systems, Soft Computing Methods for characterizing Diseases from Omics Data, Engineering Bio-Interfaces and Rudimentary Cells as a way to Develop Synthetic Biology, Modelling and Simulation Methods for System Biology and System Medicine, Fast and Efficient Solutions for Computational Intelligence Methods in Bioinformatics, Systems, and Computational Biology, Networking Biostatistics and Bioinformatics, Machine Explanation—Interpretation of Machine Learning Models for Medicine and Bioinformatics. The organization of this edition of CIBB was supported by the Department of Informatics, Systems and Communication of the University of Milano-Bicocca, Italy, and by the Institute of Biomedical Technologies of the National Research Council, Italy. Besides the papers focused on computational intelligence methods applied to open problems of bioinformatics and biostatistics, the works submitted to CIBB 2019 dealt with algebraic and computational methods to study RNA behaviour, intelligence methods for molecular characterization and dynamics in translational medicine, modeling and simulation methods for computational biology and systems medicine, and machine learning in healthcare informatics and medical biology.