Author: Andrew Schumann

Affiliation: University of Information Technology and Management in Rzeszow, Poland

ISBN: 978-989-758-310-0

Abstract: Artificial actin filament networks (AAFN) we are going to design employ transmitting information by means of building and rebuilding actin filaments in responses to dynamics of intra-cellular and extra-cellular stimuli. Actin is one of the most important proteins responsible for a reaction of cells to different stresses including internal and external. In responses to stimuli, filaments can be organized as complex networks of different forms: (i) unstable bunches forming a filament wave, (ii) trees supporting the membrane or changing it to pseudopodia, (iii) stable bunches for transmitting mechanical forces. For designing protein robots, we are interested in managing reactions of AAFN by modeling external stimuli. There are the following two basic types of all the external stimuli: (i) attractants (which stimulate the directed movement towards signals by means of building and rebuilding actin filament waves towards the signals) and (ii) repellents (which stimulate the directed movemen t away from signals by means of building and rebuilding actin filament waves in the opposite direction). In this model, we have inputs as different stresses and outputs as assemblies and disassemblies of actin filament waves. Thus, under different external conditions we observe different dynamics in changing the outlook of AAFN. In this way AAFN can be represented as a basic mechanism of the primitive protein robots, in which actin filament waves are regarded as processors. These processors can appear in one setting and they can disappear in other settings. The system of AAFN is much more complex and effective, than artificial neural networks studied well. The point is that in artificial neural networks, there is a fixed number of processors (called neurons) and there are many connections among neurons which are changeable. In the AAFN, both processors (called actin filament waves) and all the connections among them are changeable simultaneously. As a result, the AAFN can solve much more tasks, than artificial neural networks. Now there is no mathematical theory of AAFN. Nevertheless, if it is possible to create an artificial protein broth which will be a robot solving the complex of various tasks (learning, orientation in space, moving, decision making about own transitions, etc.), then this broth will consist of actin filaments controlled by us. In the project for the first time we are going to propose a mathematical theory of AAFN which can be used for designing communication networks organized among mobile agents, communicated in large groups which can joint higher-order groups, as well. (More)

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Paper citation in several formats:
Schumann A. and (2017). Protein Robots Designed on Actin Filament Networks.In European Project Space on Networks, Systems and Technologies - Volume 1: EPS Porto 2017, ISBN 978-989-758-310-0, pages 3-27. DOI: 10.5220/0007902100030027

@conference{eps porto 201717,
author={Andrew Schumann},
title={Protein Robots Designed on Actin Filament Networks},
booktitle={European Project Space on Networks, Systems and Technologies - Volume 1: EPS Porto 2017,},


JO - European Project Space on Networks, Systems and Technologies - Volume 1: EPS Porto 2017,
TI - Protein Robots Designed on Actin Filament Networks
SN - 978-989-758-310-0
AU - Schumann, A.
PY - 2017
SP - 3
EP - 27
DO - 10.5220/0007902100030027

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