IJCIBSB special issue 2008

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IJCIBSB special issue 2008
Classify the Classifiers: Investigating the Optimum Classification Technique Per Case in Bioinformatics
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Homepage:	www.inderscience.com/browse/callpaper.php?callID=859
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Important dates
Submissions:	Mar 31, 2008
Table of Contents

CClassify the Classifiers: Investigating the Optimum Classification Technique Per Case in Bioinformatics

A special issue of International Journal of Computational Intelligence in Bioinformatics and Systems Biology

Suitable topics include, but are not limited to:
** Investigation and ranking of classifiers based on, but not limited to, computational intelligence methods from fields such as:

    * Machine learning
    * Expert systems
    * Artificial neural networks
    * Fuzzy logic and systems
    * Feature selection
    * Dimension reduction
    * Pattern classification and recognition
    * Possibility theory
    * Bayes network and hidden markov models
    * Genetic and [hybrid] evolutionary algorithms
    * Support vector machines
    * Relative vector machine
    * Data mining and knowledge discoveries
    * Quantum-inspired evolutionary algorithms
    * Fusion of systems
    * Swarm intelligence and hybrid computational intelligence
    * Affinity propagation
    * Game theory

** Application and performance evaluation of the classifiers implemented in various cases of bioinformatics research, such as:

    * Gene expression
    * Microarrays, motif and pattern discovery
    * DNA assembly, clustering, and mapping
    * Gene identification and annotation
    * Biomedical image processing
    * Molecular evolution and phylogeny
    * Taxonomy, sequence analysis and alignment
    * Ecological modelling
    * Mathematical immunology modelling and discovery
    * Regulatory network and pathway analysis
    * Functional and structural genomics
    * Cellular metabolism and inter-cellular signalling
    * Genome- and proteome-scale modelling
    * Analysis of protein interaction with other cellular constituents
    * Protein structure and interaction prediction
    * Comparative and quantitative proteomics
    * Post-translational modification analysis
    * Structural proteomics
	

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