Computational Intelligence Methods for Bioinformatics and Biostatistics: 16th International Meeting, CIBB 2019, Bergamo, Italy, September 4–6, 2019, Revised Selected Papers

Author:   Paolo Cazzaniga ,  Daniela Besozzi ,  Ivan Merelli ,  Luca Manzoni
Publisher:   Springer Nature Switzerland AG
Edition:   1st ed. 2020
Volume:   12313
ISBN:  

9783030630607


Pages:   350
Publication Date:   10 December 2020
Format:   Paperback
Availability:   Manufactured on demand   Availability explained
We will order this item for you from a manufactured on demand supplier.

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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


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Overview

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.

Full Product Details

Author:   Paolo Cazzaniga ,  Daniela Besozzi ,  Ivan Merelli ,  Luca Manzoni
Publisher:   Springer Nature Switzerland AG
Imprint:   Springer Nature Switzerland AG
Edition:   1st ed. 2020
Volume:   12313
Weight:   0.557kg
ISBN:  

9783030630607


ISBN 10:   3030630609
Pages:   350
Publication Date:   10 December 2020
Audience:   Professional and scholarly ,  Professional & Vocational
Format:   Paperback
Publisher's Status:   Active
Availability:   Manufactured on demand   Availability explained
We will order this item for you from a manufactured on demand supplier.

Table of Contents

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 Alzheimer’s 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 Accelerating Smith-Waterman Execution of GATK HaplotypeCaller.- Algebraic and Computational Methods for the Study of RNA Behaviour.- Algebraic Characterisation of Non-coding RNA 141 Bi-Alignments as Models of Incongruent Evolution of RNA Sequence and Secondary Structure.- Label Core for Understanding RNA Structures.- Modification of Valiant’s Parsing Algorithm for the String-Searching Problem.- On Secondary Structure Analysis by Using Formal Grammars and Artificial Neural Networks.- Intelligence methods for molecular characterization and dynamics in translational medicine.- Integration of single-cell RNA-sequencing data into flux balance cellular automata.- Machine Learning in Healthcare Informatics and Medical Biology.- Characterizing bipolar disorder-associated single nucleotide polymorphisms ina large UK cohort using Association Rules.- Evaluating deep semi-supervised learning for whole-transcriptome breast cancer subtyping.- Learning Weighted Association Rules in Human Phenotype Ontology.- Network modeling and analysis of normal and cancer gene expression data.- Regularization techniques in Radiomics: A case study on the prediction of pCR in Breast Tumours and the Axilla.- Modeling and Simulation Methods for Computational Biology and Systems Medicine.- In Silico evaluation of daclizumab and vitamin D effects in Multiple Sclerosis using Agent Based Models.- Multiple Sclerosis disease: a computational approach for investigating its drug interactions.- Observability of bacterial growth models in bubble column bioreactors.- On the simulation and automatic parametrization of metabolic networks through Electronic Design Automation.

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