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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
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Computational Intelligence Methods for Bioinformatics and Biostatistics
Published by
Springer International Publishing, January 2016
DOI 10.1007/978-3-319-44332-4
978-3-31-944331-7, 978-3-31-944332-4

De Baets, Leen, Van Gassen, Sofie, Dhaene, Tom, Saeys, Yvan


Claudia Angelini, Paola MV Rancoita, Stefano Rovetta

Twitter Demographics

The data shown below were collected from the profiles of 2 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 80 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 80 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 2 3%
Student > Postgraduate 1 1%
Researcher 1 1%
Unspecified 1 1%
Unknown 75 94%
Readers by discipline Count As %
Environmental Science 1 1%
Unspecified 1 1%
Earth and Planetary Sciences 1 1%
Psychology 1 1%
Chemistry 1 1%
Other 0 0%
Unknown 75 94%