• [Photo] David Pelta May 2, 2003
    Call for papers: Journal of Fuzzy Sets and Systems, special issue on fuzzy sets and systems in bioinformatics

    Important Dates:
    • Deadline for Submission: Dec, 15 2003
    • Notification of acceptance: March, 20 2004
    • Deadline for final version (in elsevier latex format): May, 1 2004
    A forthcoming issue of the Journal of Fuzzy Sets and Systems will be devoted to provide the state-of-art in the application of fuzzy sets and systems to bioinformatics, highlighting new and promising research areas.

    Bioinformatics lies at the interface between biology, computer science and information technology. The ultimate goal of the field is to enable the discovery of new biological insights as well as to create a global perspective from which unifying principles in biology could be discerned. Moreover, Computational and mathematical insights gained in the pursuit of bioinformatics excellence have already impacted on other areas of the mathematical and computer sciences.

    The application of fuzzy sets and systems (FSS) to bioinformatics gives raise to an emergent area that is growing fast as both scientific communities met. The use of FSS in Bioinformatics could be fruitful in at least two ways:
    • Providing the formal tools to deal with the aspects of uncertainty, vagueness and fuzziness that are inherent to bioinformatics problems
    • Improving reliability and robustness by hybridising with other optimisation/machine learning techniques
    The purpose of this special issue is to highlight and explore some of the more recent theoretical and practical advances in the field of Fuzzy Sets and Systems with an application to Bioinformatics and Computational Biology.

    Original, high-quality papers providing insights and results on the application of FSS to bioinformatics are sought, addressing issues including (but not restricted to):
    • Theoretical methods and models for FSS in bioinformatics.
    • Novel hybridisation methods with other optimisation/machine learning techniques.
    • Data mining, Knowledge discovery and interpretation of biological data repositories.
    • Phylogenetic reconstruction
    • Structure/Sequence analysis/prediction for bio-molecules.
    • Performance comparisons with other optimisation/machine learning techniques.
    • Network reconstruction for development, expression, metabolism, catalysis, regulation, etc.
    • Methodologies/philosophy/pedagogy of bioinformatics as a multidisciplinary activity.
    • hardware implementation of fuzzy or fuzzy/hybrid systems for bioinformatics applications
    For more information, see the journal web page:
    http://www.elsevier.nl/locate/fss

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