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Applications of Computational Intelligence in Biology

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Table of Contents

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    Book Overview
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    Chapter 1 Statistically Based Pattern Discovery Techniques for Biological Data Analysis
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    Chapter 2 Rough Sets In Data Analysis: Foundations and Applications
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    Chapter 3 Evolving Solutions: The Genetic Algorithm and Evolution Strategies for Finding Optimal Parameters
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    Chapter 4 An Introduction to Multi-Objective Evolutionary Algorithms and Some of Their Potential Uses in Biology
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    Chapter 5 Local Classifiers as a Method of Analysing and Classifying Signals
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    Chapter 6 Using Neural Models for Evaluation of Biological Activity of Selected Chemical Compounds
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    Chapter 7 Using Machine Vision to Detect Distinctive Behavioral Phenotypes of Thread-shape Microscopic Organism
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    Chapter 8 Contour Matching for Fish Species Recognition and Migration Monitoring
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    Chapter 9 Applications of Computational Intelligence in Biology
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    Chapter 10 Visualization and Interactive Exploration of Large, Multidimensional Data Sets
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    Chapter 11 Phylogenomics, Protein Family Evolution, and the Tree of Life: An Integrated Approach between Molecular Evolution and Computational Intelligence
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    Chapter 12 Computational Aspects of Aggregation in Biological Systems
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    Chapter 13 Conceptual Biology Research Supporting Platform: Current Design and Future Directions
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    Chapter 14 Computational Intelligence in Electrophysiology: Trends and Open Problems
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    Chapter 15 Using Broad Cognitive Models to Apply Computational Intelligence to Animal Cognition
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    Chapter 16 Applications of Computational Intelligence in Biology
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Citations

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Title
Applications of Computational Intelligence in Biology
Published by
Springer Berlin Heidelberg, May 2008
DOI 10.1007/978-3-540-78534-7
ISBNs
978-3-54-078533-0, 978-3-54-078534-7
Editors

Smolinski, Tomasz G., Milanova, Mariofanna G., Hassanien, Aboul-Ella

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X Demographics

The data shown below were collected from the profiles of 4 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 42 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Malaysia 2 5%
Egypt 1 2%
Ireland 1 2%
United States 1 2%
Unknown 37 88%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 13 31%
Researcher 9 21%
Student > Master 5 12%
Student > Bachelor 4 10%
Student > Doctoral Student 4 10%
Other 7 17%
Readers by discipline Count As %
Computer Science 12 29%
Agricultural and Biological Sciences 6 14%
Unspecified 4 10%
Physics and Astronomy 3 7%
Mathematics 3 7%
Other 14 33%