Computational Intelligence Methods for Bioinformatics and Biostatistics: 16th International Meeting, CIBB 2019, Bergamo, Italy, September 46, 2019, R [Paperback]

This book constitutes revised selected papers from the 16^th International Meeting on Computational Intelligence Methods for Bioinformatics and Biostatistics, CIBB 2019, which was held in Bergamo, Italy, during September 4-6, 2019.

The 28 full papers presented in this volume were carefully reviewed and selected from 55 submissions. The papers are grouped in topical sections as follows: Computational Intelligence Methods for Bioinformatics and Biostatistics; Algebraic and Computational Methods for the Study of RNA Behaviour; Intelligence methods for molecular characterization medicine; Machine Learning in Healthcare Informatics and Medical Biology; Modeling and Simulation Methods for Computational Biology and Systems Medicine.

Computational Intelligence Methods for Bioinformatics and Biostatistics.- A Smartphone-Based Clinical Decision Support System for Tremor Assessment.- cyTRON and cyTRON/JS: two Cytoscape-based applications for the inference of cancer evolution models.- Effective use of evolutionary computation to parameterise an epidemiological model.- Extending knowledge on genomic data and metadata of cancer by exploiting taxonomy-based relaxed queries on domain-specific ontologies.- GAN-Based Multiple Adjacent Brain MRI Slice Reconstruction for Unsupervised Alzheimers Disease Diagnosis.- Improving the Fusion of Outbreak Detection Methods with Supervised Learning.- Learning cancer drug sensitivities in large-scale screens from multi-omics data with local low-rank structure.- Mass Spectra Interpretation and the Interest of SpecFit for Identifying Uncommon Modifications.- MSAX: Multivariate symbolic aggregate approximation for time series classification.- NeoHiC: a Web Application forthe Analysis of Hi-C Data 100 Random sample consensus for the robust identification of outliers in cancer data.- Solving Equations on Discrete Dynamical Systems.- SW+: On Accell³-