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Computational Intelligence Methods for Bioinformatics and Biostatistics

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Cover of 'Computational Intelligence Methods for Bioinformatics and Biostatistics'

Table of Contents

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    Book Overview
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    Chapter 1 Compressive Sensing and Hierarchical Clustering for Microarray Data with Missing Values
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    Chapter 2 Variational Inference in Probabilistic Single-cell RNA-seq Models
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    Chapter 3 Centrality Speeds the Subgraph Isomorphism Search Up in Target Aware Contexts
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    Chapter 4 Structure-Based Antibody Paratope Prediction with 3D Zernike Descriptors and SVM
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    Chapter 5 Simultaneous Phasing of Multiple Polyploids
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    Chapter 6 Classification of Epileptic Activity Through Temporal and Spatial Characterization of Intracranial Recordings
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    Chapter 7 Committee-Based Active Learning to Select Negative Examples for Predicting Protein Functions
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    Chapter 8 A Graphical Tool for the Exploration and Visual Analysis of Biomolecular Networks
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    Chapter 9 Improved Predictor-Corrector Algorithm
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    Chapter 10 Identification of Key miRNAs in Regulation of PPI Networks
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    Chapter 11 Recurrent Deep Neural Networks for Nucleosome Classification
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    Chapter 12 Searching for the Source of Difference: A Graphical Model Approach
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    Chapter 13 A New Partially Segment-Wise Coupled Piece-Wise Linear Regression Model for Statistical Network Structure Inference
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    Chapter 14 Inhibition of Primed Ebola Virus Glycoprotein by Peptide Compound Conjugated to HIV-1 Tat Peptide Through a Virtual Screening Approach
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    Chapter 15 Pharmacophore Modelling, Virtual Screening, and Molecular Docking Simulations of Natural Product Compounds as Potential Inhibitors of Ebola Virus Nucleoprotein
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    Chapter 16 Global Sensitivity Analysis of Constraint-Based Metabolic Models
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    Chapter 17 Efficient and Settings-Free Calibration of Detailed Kinetic Metabolic Models with Enzyme Isoforms Characterization
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    Chapter 18 Automatic Discrimination of Auditory Stimuli Perceived by the Human Brain
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    Chapter 19 Neural Models for Brain Networks Connectivity Analysis
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    Chapter 20 Exposing and Characterizing Subpopulations of Distinctly Regulated Genes by K-Plane Regression
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    Chapter 21 Network Propagation-Based Semi-supervised Identification of Genes Associated with Autism Spectrum Disorder
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    Chapter 22 Designing and Evaluating Deep Learning Models for Cancer Detection on Gene Expression Data
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    Chapter 23 Analysis of Extremely Obese Individuals Using Deep Learning Stacked Autoencoders and Genome-Wide Genetic Data
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    Chapter 24 Predicting the Oncogenic Potential of Gene Fusions Using Convolutional Neural Networks
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    Chapter 25 Unravelling Breast and Prostate Common Gene Signatures by Bayesian Network Learning
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    Chapter 26 Effect of Epigallocatechin-3-gallate on DMPC Oxidation Revealed by Infrared Spectroscopy
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    Chapter 27 Effect of EGCG on the DNA in Presence of UV Radiation
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    Chapter 28 Non-thermal Atmospheric Pressure Plasmas: Generation, Sources and Applications
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    Chapter 29 Adsorption of Triclosan on Sensors Based on PAH/PAZO Thin-Films: The Effect of pH
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    Chapter 30 Detection of Triclosan Dioxins After UV Irradiation – A Preliminar Study
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Title
Computational Intelligence Methods for Bioinformatics and Biostatistics
Published by
Lecture notes in computer science, January 2020
DOI 10.1007/978-3-030-34585-3
ISBNs
978-3-03-034584-6, 978-3-03-034585-3
Editors

Raposo, Maria, Ribeiro, Paulo, Sério, Susana, Staiano, Antonino, Ciaramella, Angelo

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 Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 22 January 2020.
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#19,701,336
of 24,226,848 outputs
Outputs from Lecture notes in computer science
#6,050
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#343,762
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Outputs of similar age from Lecture notes in computer science
#20
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