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Computational Intelligence Methods for Bioinformatics and Biostatistics

16th International Meeting, CIBB 2019, Bergamo, Italy, September 4–6, 2019, Revised Selected Papers

  • Conference proceedings
  • © 2020

Overview

Editors:
  1. Paolo Cazzaniga

    1. University of Bergamo, Bergamo, Italy

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  2. Daniela Besozzi

    1. University of Milano-Bicocca, Milan, Italy

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  3. Ivan Merelli

    1. National Research Council, Segrate, Italy

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  4. Luca Manzoni

    1. Università degli Studi di Trieste, Trieste, Italy

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Part of the book series: Lecture Notes in Computer Science (LNCS, volume 12313)

Part of the book sub series: Lecture Notes in Bioinformatics (LNBI)

Included in the following conference series:

Conference proceedings info: CIBB 2019.

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Table of contents (29 papers)

  1. Front Matter

    Pages i-xiv
    Download chapter PDF

  2. Computational Intelligence Methods for Bioinformatics and Biostatistics

    1. Front Matter

      Pages 1-1
      Download chapter PDF

    2. A Smartphone-Based Clinical Decision Support System for Tremor Assessment

      • Guillaume Zamora, Caro Fuchs, Aurélie Degeneffe, Pieter Kubben, Uzay Kaymak
      Pages 3-12

    3. cyTRON and cyTRON/JS: Two Cytoscape-Based Applications for the Inference of Cancer Evolution Models

      • Lucrezia Patruno, Edoardo Galimberti, Daniele Ramazzotti, Giulio Caravagna, Luca De Sano, Marco Antoniotti et al.
      Pages 13-18

    4. Effective Use of Evolutionary Computation to Parameterise an Epidemiological Model

      • Ryan Mitchell, David Cairns, Dalila Hamami, Kevin Pollock, Carron Shankland
      Pages 19-32

    5. Extending Knowledge on Genomic Data and Metadata of Cancer by Exploiting Taxonomy-Based Relaxed Queries on Domain-Specific Ontologies

      • Eleonora Cappelli, Emanuel Weitschek, Fabio Cumbo
      Pages 33-43

    6. GAN-Based Multiple Adjacent Brain MRI Slice Reconstruction for Unsupervised Alzheimer’s Disease Diagnosis

      • Changhee Han, Leonardo Rundo, Kohei Murao, Zoltán Ádám Milacski, Kazuki Umemoto, Evis Sala et al.
      Pages 44-54

    7. Improving the Fusion of Outbreak Detection Methods with Supervised Learning

      • Moritz Kulessa, Eneldo Loza Mencía, Johannes Fürnkranz
      Pages 55-66

    8. Learning Cancer Drug Sensitivities in Large-Scale Screens from Multi-omics Data with Local Low-Rank Structure

      • The Tien Mai, Leiv Rønneberg, Zhi Zhao, Manuela Zucknick, Jukka Corander
      Pages 67-79

    9. Mass Spectra Interpretation and the Interest of SpecFit for Identifying Uncommon Modifications

      • Guillaume Fertin, Matthieu David, Hélène Rogniaux, Dominique Tessier
      Pages 80-89

    10. MSAX: Multivariate Symbolic Aggregate Approximation for Time Series Classification

      • Manuel Anacleto, Susana Vinga, Alexandra M. Carvalho
      Pages 90-97

    11. NeoHiC: A Web Application for the Analysis of Hi-C Data

      • Daniele D’Agostino, Pietro Liò, Marco Aldinucci, Ivan Merelli
      Pages 98-107

    12. Random Sample Consensus for the Robust Identification of Outliers in Cancer Data

      • André Veríssimo, Marta B. Lopes, Eunice Carrasquinha, Susana Vinga
      Pages 108-118

    13. Solving Equations on Discrete Dynamical Systems

      • Alberto Dennunzio, Enrico Formenti, Luciano Margara, Valentin Montmirail, Sara Riva
      Pages 119-132

    14. SW+: On Accelerating Smith-Waterman Execution of GATK HaplotypeCaller

      • Meysam Roodi, Andreas Moshovos
      Pages 133-141

  3. Algebraic and Computational Methods for the Study of RNA Behaviour

    1. Front Matter

      Pages 143-143
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    2. Algebraic Characterisation of Non-coding RNA

      • Stefano Maestri, Emanuela Merelli
      Pages 145-158

    3. Bi-alignments as Models of Incongruent Evolution of RNA Sequence and Secondary Structure

      • Maria Waldl, Sebastian Will, Michael T. Wolfinger, Ivo L. Hofacker, Peter F. Stadler
      Pages 159-170

    4. Label Core for Understanding RNA Structure

      • Michela Quadrini, Emanuela Merelli, Riccardo Piergallini
      Pages 171-179

    5. Modification of Valiant’s Parsing Algorithm for the String-Searching Problem

      • Yuliya Susanina, Anna Yaveyn, Semyon Grigorev
      Pages 180-192
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  1. Computational Intelligence Methods for Bioinformatics and Biostatistics

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About this book

This book constitutes revised selected papers from the 16th 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.

Editors and Affiliations

  • University of Bergamo, Bergamo, Italy

    Paolo Cazzaniga

  • University of Milano-Bicocca, Milan, Italy

    Daniela Besozzi

  • National Research Council, Segrate, Italy

    Ivan Merelli

  • Università degli Studi di Trieste, Trieste, Italy

    Luca Manzoni

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