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Fuzzy Causal Mapping (F-Cmap) — A Proposal To Develop A New Systems Biology Tool

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Author Info

  • GABRIEL WEINREB

    ()
    (Department of Cell and Developmental Biology, CB #7090, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA)

  • PAUL Y. CAO

    (Department of Computer Science, Ashland University, 401 College Avenue Ashland, OH 44805, USA)

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    Abstract

    Biological systems are complex, consisting of many elements of different nature. As a whole, they are robust, and a general system description can be done in a semi-quantitative way when it comes to phenotype behaviors. We used these properties earlier1 to develop a new systems biology method, causal mapping (CMAP). In this paper, we pinpoint some problems with the earlier version of CMAP, and develop it further. CMAP used linguistic variables (LV) to describe the behaviour of biological systems, and here we use the procedure of fuzzyfications to improve CMAP. The numerical methods to calculate the ranges of LV are agreeable to reality in a very intuitive manner. The new version of CMAP reproduced the physical data on cortical oscillations2 in spreading cells with depolymerized microtubules. Further, predictions were made on the dependency of the myosin activity on the period of oscillations.The presented development lies on the way to a more general approach that should be able to address questions of biological robustness, modularity and hierarchy.

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    Bibliographic Info

    Article provided by World Scientific Publishing Co. Pte. Ltd. in its journal New Mathematics and Natural Computation.

    Volume (Year): 06 (2010)
    Issue (Month): 01 ()
    Pages: 97-107

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    Handle: RePEc:wsi:nmncxx:v:06:y:2010:i:01:p:97-107

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    Related research

    Keywords: Causal mapping (CMAP); fuzzy CMAP; linguistic variable; systems biology;

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