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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 Modelling the Effect of Genes on the Dynamics of Probabilistic Spiking Neural Networks for Computational Neurogenetic Modelling
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    Chapter 2 Biostatistics Meets Bioinformatics in Integrating Information from Highdimensional Heterogeneous Genomic Data: Two Examples from Rare Genetic Diseases and Infectious Diseases
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    Chapter 3 Bayesian Models for the Multi-sample Time-Course Microarray Experiments
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    Chapter 4 A Machine Learning Pipeline for Discriminant Pathways Identification
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    Chapter 5 Discovering Hidden Pathways in Bioinformatics
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    Chapter 6 Reliability of miRNA Microarray Platforms: An Approach Based on Random Effects Linear Models
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    Chapter 7 Computational Intelligence Methods for Bioinformatics and Biostatistics
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    Chapter 8 Feature Selection for the Prediction and Visualization of Brain Tumor Types Using Proton Magnetic Resonance Spectroscopy Data
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    Chapter 9 On the Use of Graphical Models to Study ICU Outcome Prediction in Septic Patients Treated with Statins
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    Chapter 10 Integration of Biomolecular Interaction Data in a Genomic and Proteomic Data Warehouse to Support Biomedical Knowledge Discovery
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    Chapter 11 Machine-Learning Methods to Predict Protein Interaction Sites in Folded Proteins
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    Chapter 12 Complementing Kernel-Based Visualization of Protein Sequences with Their Phylogenetic Tree
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    Chapter 13 DEEN: A Simple and Fast Algorithm for Network Community Detection
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    Chapter 14 Self-similarity in Physiological Time Series: New Perspectives from the Temporal Spectrum of Scale Exponents
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    Chapter 15 Support Vector Machines for Survival Regression
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    Chapter 16 Boosted C5 Trees i-Biomarkers Panel for Invasive Bladder Cancer Progression Prediction
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    Chapter 17 A Faster Algorithm for Motif Finding in Sequences from ChIP-Seq Data
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    Chapter 18 Case/Control Prediction from Illumina Methylation Microarray’s β and Two-Color Channels in the Presence of Batch Effects
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    Chapter 19 Supporting the Design, Communication and Management of Bioinformatic Protocols through the Leaf Tool
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    Chapter 20 Genomic Annotation Prediction Based on Integrated Information
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    Chapter 21 Solving Biclustering with a GRASP-Like Metaheuristic: Two Case-Studies on Gene Expression Analysis
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Title
Computational Intelligence Methods for Bioinformatics and Biostatistics
Published by
Springer, Berlin, Heidelberg, January 2011
DOI 10.1007/978-3-642-35686-5
ISBNs
978-3-64-235685-8, 978-3-64-235686-5
Editors

Elia Biganzoli, Alfredo Vellido, Federico Ambrogi, Roberto Tagliaferri

Mendeley readers

The data shown below were compiled from readership statistics for 120 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 120 100%

Demographic breakdown

Readers by professional status Count As %
Student > Master 2 2%
Student > Ph. D. Student 1 <1%
Unknown 117 98%
Readers by discipline Count As %
Computer Science 2 2%
Engineering 1 <1%
Unknown 117 98%