FUZZY CAUSAL MAPPING (F-CMAP) - A PROPOSAL TO DEVELOP A NEW SYSTEMS BIOLOGY TOOL

Title:

FUZZY CAUSAL MAPPING (F-CMAP) - A PROPOSAL TO DEVELOP A NEW SYSTEMS BIOLOGY TOOL
Supported by NIH GM073180 (Tim Elston, Ken Jacobson, Gabriel Weinreb (UNC-CH)) and NIH Cell Migration Consortium GM64346 (Ken Jacobson).

DOI No:

10.1142/9789812709677_0022

Source:

INFORMATION SCIENCES 2007 (pp 144-156)

Author(s):

GABRIEL WEINREB
To whom requests for reprints should be addressed.
Tel: (919) 966-3855.
Department of Cell and Developmental Biology, CB #7090, University of North Carolina at Chapel Hill, Chapel Hill, NC, 27599, USA
YINGJUN CAO
Tel: (919) 530-6237.
Department of Computer Science, North Carolina Central University, 1801 Fayetteville Street, Durham NC 27707, USA

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 earlier [1] 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 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 oscillations [2] 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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