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Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics

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Cover of 'Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics'

Table of Contents

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    Book Overview
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    Chapter 1 Multiple Threshold Spatially Uniform ReliefF for the Genetic Analysis of Complex Human Diseases
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    Chapter 2 Time-Point Specific Weighting Improves Coexpression Networks from Time-Course Experiments
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    Chapter 3 Inferring Human Phenotype Networks from Genome-Wide Genetic Associations
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    Chapter 4 Knowledge-Constrained K-Medoids Clustering of Regulatory Rare Alleles for Burden Tests
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    Chapter 5 Feature Selection and Classification of High Dimensional Mass Spectrometry Data: A Genetic Programming Approach
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    Chapter 6 Structured Populations and the Maintenance of Sex
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    Chapter 7 Hybrid Multiobjective Artificial Bee Colony with Differential Evolution Applied to Motif Finding
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    Chapter 8 ACO-Based Bayesian Network Ensembles for the Hierarchical Classification of Ageing-Related Proteins
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    Chapter 9 Dimensionality Reduction via Isomap with Lock-Step and Elastic Measures for Time Series Gene Expression Classification
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    Chapter 10 Supervising Random Forest Using Attribute Interaction Networks
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    Chapter 11 Hybrid Genetic Algorithms for Stress Recognition in Reading
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    Chapter 12 Optimal Use of Biological Expert Knowledge from Literature Mining in Ant Colony Optimization for Analysis of Epistasis in Human Disease
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    Chapter 13 A Multiobjective Proposal Based on the Firefly Algorithm for Inferring Phylogenies
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    Chapter 14 Mining for Variability in the Coagulation Pathway: A Systems Biology Approach
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    Chapter 15 Improving the Performance of CGPANN for Breast Cancer Diagnosis Using Crossover and Radial Basis Functions
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    Chapter 16 An Evolutionary Approach to Wetlands Design
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    Chapter 17 Impact of Different Recombination Methods in a Mutation-Specific MOEA for a Biochemical Application
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    Chapter 18 Cell-Based Metrics Improve the Detection of Gene-Gene Interactions Using Multifactor Dimensionality Reduction
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    Chapter 19 Emergence of Motifs in Model Gene Regulatory Networks
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1 Wikipedia page


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Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics
Published by
Springer, Berlin, Heidelberg, January 2013
DOI 10.1007/978-3-642-37189-9
978-3-64-237188-2, 978-3-64-237189-9

Leonardo Vanneschi, William S. Bush, Mario Giacobini

Twitter Demographics

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Mendeley readers

The data shown below were compiled from readership statistics for 8 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 1 13%
Colombia 1 13%
Unknown 6 75%

Demographic breakdown

Readers by professional status Count As %
Researcher 3 38%
Student > Ph. D. Student 2 25%
Student > Doctoral Student 1 13%
Student > Master 1 13%
Other 1 13%
Other 0 0%
Readers by discipline Count As %
Computer Science 4 50%
Agricultural and Biological Sciences 2 25%
Business, Management and Accounting 1 13%
Chemistry 1 13%