2016 IEEE International Conference on Fuzzy Systems (FUZZ) , 2016-07-24

Title : ( Fuzzy-CA Model for an In-silico Cancer Cell Line: A Journey from Simple Cellular Pattern to an Emergent Complex Behavior )

Authors: Nasibeh Rady Raz , Mohammad Reza Akbarzadeh Totonchi ,

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Abstract

Cancer is a complex disease which is composed of numerous interactive components that operate in an environment with high uncertainties. Approaching such a system hence requires its own set of tools. Here, we propose an in-silico model of cancer cell line based on local environmental information, and study its emergent complex global cellular behaviors. The proposed model is composed of a Fuzzy Inference System (FIS) and a Cellular Automata (CA). The FIS has five inputs including nutrition concentration, cell density, apoptosis rate, Vascular Endothelial Growth Factor (VEGF) concentration, and H+ ion concentration. The output of the proposed FIS is the cell state parameter. The FIS determines a threshold as the input of the CA for extracting the appropriate cellular patterns. The generated cellular patterns are based only on local information, but the overall system exhibits a global behavior. The merit of the model is in the simplicity of the rules in learning the complex global system behaviors.

Keywords

Targeted Cancer Therapy; Complex System; Insilico Cell Line; Cellular Automata;
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@inproceedings{paperid:1067537,
author = {Rady Raz, Nasibeh and Akbarzadeh Totonchi, Mohammad Reza},
title = {Fuzzy-CA Model for an In-silico Cancer Cell Line: A Journey from Simple Cellular Pattern to an Emergent Complex Behavior},
booktitle = {2016 IEEE International Conference on Fuzzy Systems (FUZZ)},
year = {2016},
location = {Vancouver},
keywords = {Targeted Cancer Therapy; Complex System; Insilico Cell Line; Cellular Automata;},
}

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%0 Conference Proceedings
%T Fuzzy-CA Model for an In-silico Cancer Cell Line: A Journey from Simple Cellular Pattern to an Emergent Complex Behavior
%A Rady Raz, Nasibeh
%A Akbarzadeh Totonchi, Mohammad Reza
%J 2016 IEEE International Conference on Fuzzy Systems (FUZZ)
%D 2016

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