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Computational Intelligence Methods for Bioinformatics and Biostatistics

15th International Meeting, CIBB 2018, Caparica, Portugal, September 6–8, 2018, Revised Selected Papers

  • Conference proceedings
  • © 2020

Overview

Editors:
  1. Maria Raposo

    1. Universidade Nova de Lisboa, Caparica, Portugal

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  2. Paulo Ribeiro

    1. Universidade Nova de Lisboa, Caparica, Portugal

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  3. Susana Sério

    1. University of Lisbon, Caparica, Portugal

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  4. Antonino Staiano

    1. Università degli Studi di Napoli Parthenope, Naples, Italy

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  5. Angelo Ciaramella

    1. Università degli Studi di Napoli Parthenope, Naples, Italy

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Part of the book series: Lecture Notes in Computer Science (LNCS, volume 11925)

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

Included in the following conference series:

Conference proceedings info: CIBB 2018.

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Table of contents (31 papers)

  1. Front Matter

    Pages i-xxii
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  2. Computational Intelligence Methods for Bioinformatics and Biostatistics

    1. Front Matter

      Pages 1-1
      Download chapter PDF

    2. Compressive Sensing and Hierarchical Clustering for Microarray Data with Missing Values

      • Angelo Ciaramella, Davide Nardone, Antonino Staiano
      Pages 3-10

    3. Variational Inference in Probabilistic Single-cell RNA-seq Models

      • Pedro F. Ferreira, Alexandra M. Carvalho, Susana Vinga
      Pages 11-18

    4. Centrality Speeds the Subgraph Isomorphism Search Up in Target Aware Contexts

      • Vincenzo Bonnici, Simone Caligola, Antonino Aparo, Rosalba Giugno
      Pages 19-26

    5. Structure-Based Antibody Paratope Prediction with 3D Zernike Descriptors and SVM

      • Sebastian Daberdaku
      Pages 27-49

    6. Simultaneous Phasing of Multiple Polyploids

      • Laxmi Parida, Filippo Utro
      Pages 50-68

    7. Classification of Epileptic Activity Through Temporal and Spatial Characterization of Intracranial Recordings

      • Vanessa D’Amario, Gabriele Arnulfo, Lino Nobili, Annalisa Barla
      Pages 69-79

    8. Committee-Based Active Learning to Select Negative Examples for Predicting Protein Functions

      • Marco Frasca, Maryam Sepehri, Alessandro Petrini, Giuliano Grossi, Giorgio Valentini
      Pages 80-87

    9. A Graphical Tool for the Exploration and Visual Analysis of Biomolecular Networks

      • Cheick Tidiane Ba, Elena Casiraghi, Marco Frasca, Jessica Gliozzo, Giuliano Grossi, Marco Mesiti et al.
      Pages 88-98

    10. Improved Predictor-Corrector Algorithm

      • Hassan Pazira
      Pages 99-106

    11. Identification of Key miRNAs in Regulation of PPI Networks

      • Antonino Fiannaca, Laura La Paglia, Massimo La Rosa, Giosué Lo Bosco, Riccardo Rizzo, Alfonso Urso
      Pages 107-117

    12. Recurrent Deep Neural Networks for Nucleosome Classification

      • Domenico Amato, Mattia Antonino Di Gangi, Giosuè Lo Bosco, Riccardo Rizzo
      Pages 118-127

  3. Modeling and Simulation Methods in System Biology

    1. Front Matter

      Pages 129-129
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    2. Searching for the Source of Difference: A Graphical Model Approach

      • Vera Djordjilović, Monica Chiogna, Chiara Romualdi, Elisa Salviato
      Pages 131-138

    3. A New Partially Segment-Wise Coupled Piece-Wise Linear Regression Model for Statistical Network Structure Inference

      • Mahdi Shafiee Kamalabad, Marco Grzegorczyk
      Pages 139-152

    4. Inhibition of Primed Ebola Virus Glycoprotein by Peptide Compound Conjugated to HIV-1 Tat Peptide Through a Virtual Screening Approach

      • Ahmad Husein Alkaff, Mutiara Saragih, Mochammad Arfin Fardiansyah Nasution, Usman Sumo Friend Tambunan
      Pages 153-165

    5. Pharmacophore Modelling, Virtual Screening, and Molecular Docking Simulations of Natural Product Compounds as Potential Inhibitors of Ebola Virus Nucleoprotein

      • Mochammad Arfin Fardiansyah Nasution, Ahmad Husein Alkaff, Ilmi Fadhilah Rizki, Ridla Bakri, Usman Sumo Friend Tambunan
      Pages 166-178

    6. Global Sensitivity Analysis of Constraint-Based Metabolic Models

      • Chiara Damiani, Dario Pescini, Marco S. Nobile
      Pages 179-186

    7. Efficient and Settings-Free Calibration of Detailed Kinetic Metabolic Models with Enzyme Isoforms Characterization

      • Niccolò Totis, Andrea Tangherloni, Marco Beccuti, Paolo Cazzaniga, Marco S. Nobile, Daniela Besozzi et al.
      Pages 187-202
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  1. Computational Intelligence Methods for Bioinformatics and Biostatistics

Keywords

About this book

This book constitutes the thoroughly refereed post-conference proceedings of the 15th International Meeting on Computational Intelligence Methods for Bioinformatics and Biostatistics., CIBB 2018, held in Caparica, Portugal, in September 2018. The 32 revised full papers were carefully reviewed and selected from 51 submissions. The papers present current trends at the edge of computer and life sciences, the application of computational intelligence to a system and synthetic biology and the consequent impact on innovative medicine were presented. Theoretical and experimental biologists also presented novel challenges and fostered multidisciplinary collaboration aiming to blend theory and practice, where the founding theories of the techniques used for modelling and analyzing biological systems are investigated and used for practical applications and the supporting technologies.

Editors and Affiliations

  • Universidade Nova de Lisboa, Caparica, Portugal

    Maria Raposo, Paulo Ribeiro

  • University of Lisbon, Caparica, Portugal

    Susana Sério

  • Università degli Studi di Napoli Parthenope, Naples, Italy

    Antonino Staiano, Angelo Ciaramella

Bibliographic Information

  • Book Title: Computational Intelligence Methods for Bioinformatics and Biostatistics

  • Book Subtitle: 15th International Meeting, CIBB 2018, Caparica, Portugal, September 6–8, 2018, Revised Selected Papers

  • Editors: Maria Raposo, Paulo Ribeiro, Susana Sério, Antonino Staiano, Angelo Ciaramella

  • Series Title: Lecture Notes in Computer Science

  • DOI: https://doi.org/10.1007/978-3-030-34585-3

  • Publisher: Springer Cham

  • eBook Packages: Computer Science, Computer Science (R0)

  • Copyright Information: Springer Nature Switzerland AG 2020

  • Softcover ISBN: 978-3-030-34584-6Published: 23 January 2020

  • eBook ISBN: 978-3-030-34585-3Published: 22 January 2020

  • Series ISSN: 0302-9743

  • Series E-ISSN: 1611-3349

  • Edition Number: 1

  • Number of Pages: XXII, 334

  • Number of Illustrations: 23 b/w illustrations, 111 illustrations in colour

  • Topics: Computational Biology/Bioinformatics, Artificial Intelligence, Mathematics of Computing

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