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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
Attention for Chapter 19: Emergence of Motifs in Model Gene Regulatory Networks
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Citations

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Chapter title
Emergence of Motifs in Model Gene Regulatory Networks
Chapter number 19
Book title
Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics
Published by
Springer, Berlin, Heidelberg, April 2013
DOI 10.1007/978-3-642-37189-9_19
Book ISBNs
978-3-64-237188-2, 978-3-64-237189-9
Authors

Marcin Zagórski

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 3 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Austria 1 33%
Unknown 2 67%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 1 33%
Researcher 1 33%
Student > Doctoral Student 1 33%
Readers by discipline Count As %
Computer Science 1 33%
Agricultural and Biological Sciences 1 33%
Psychology 1 33%

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