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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 A Commentary on a Censored Regression Estimator
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    Chapter 2 Selecting Random Effect Components in a Sparse Hierarchical Bayesian Model for Identifying Antigenic Variability
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    Chapter 3 Comparison of Gene Expression Signature Using Rank Based Statistical Inference
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    Chapter 4 Managing NGS Differential Expression Uncertainty with Fuzzy Sets
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    Chapter 5 Module Detection in Dynamic Networks by Temporal Edge Weight Clustering
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    Chapter 6 A Novel Technique for Reduction of False Positives in Predicted Gene Regulatory Networks
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    Chapter 7 Unsupervised Trajectory Inference Using Graph Mining
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    Chapter 8 Supervised Term Weights for Biomedical Text Classification: Improvements in Nearest Centroid Computation
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    Chapter 9 Alignment Free Dissimilarities for Nucleosome Classification
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    Chapter 10 A Deep Learning Approach to DNA Sequence Classification
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    Chapter 11 Clustering Protein Structures with Hadoop
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    Chapter 12 Comparative Analysis of MALDI-TOF Mass Spectrometric Data in Proteomics: A Case Study
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    Chapter 13 Binary Particle Swarm Optimization Versus Hybrid Genetic Algorithm for Inferring Well Supported Phylogenetic Trees
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    Chapter 14 Computing Discrete Fine-Grained Representations of Protein Surfaces
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    Chapter 15 The Challenges of Interpreting Phosphoproteomics Data: A Critical View Through the Bioinformatics Lens
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    Chapter 16 Bioinformatics Challenges and Potentialities in Studying Extreme Environments
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    Chapter 17 Improving Genome Assemblies Using Multi-platform Sequence Data
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    Chapter 18 Validation Pipeline for Computational Prediction of Genomics Annotations
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    Chapter 19 Advantages and Limits in the Adoption of Reproducible Research and R-Tools for the Analysis of Omic Data
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    Chapter 20 NuchaRt: Embedding High-Level Parallel Computing in R for Augmented Hi-C Data Analysis
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    Chapter 21 A Web Resource on Skeletal Muscle Transcriptome of Primates
Attention for Chapter 5: Module Detection in Dynamic Networks by Temporal Edge Weight Clustering
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Chapter title
Module Detection in Dynamic Networks by Temporal Edge Weight Clustering
Chapter number 5
Book title
Computational Intelligence Methods for Bioinformatics and Biostatistics
Published in
Lecture notes in computer science, July 2016
DOI 10.1007/978-3-319-44332-4_5
Book ISBNs
978-3-31-944331-7, 978-3-31-944332-4
Authors

Paola Lecca, Angela Re

Editors

Claudia Angelini, Paola MV Rancoita, Stefano Rovetta