Modelling Epigenetic Mechanisms to Capture Dynamical Topological Morphology : Applications in Edge Detection

By the same authors

Using Epigenetic Networks for the Analysis of Movement Associated with Levodopa Therapy for Parkinson's Disease
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Article in Biosystems
Evolving efficient solutions to complex problems using the Artificial Epigenetic Network
Turner, A. P., Trefzer, M. A., Lones, M. A. & Tyrrell, A., 2015, Information Processing in Cells and Tissues: 10th International Conference, IPCAT 2015, San Diego, CA, USA, September 14-16, 2015, Proceedings. Lones, M., Tyrrell, A., Smith, S. & Fogel, G. (eds.). Springer, p. 153-165 (Lecture Notes in Computer Science; vol. 9303).
Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
Operating Beyond FPGA Tool Limitations: Nervous Systems for Embedded Runtime Management
Rowlings, M., Tyrrell, A. & Trefzer, M. A., 2 Feb 2021, DATE '21: Proceedings of the 24th Conference on Design, Automation and Test in Europe. IEEE
Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
Embedded Social Insect-Inspired Intelligence Networks for System-level Runtime Management
Rowlings, M., Tyrrell, A. & Trefzer, M. A., 9 Mar 2020, Design, Automation and Test in Europe Conference: DATE2020. Grenoble, France
Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
Evolutionary acquisition of complex traits in artificial epigenetic networks
Turner, A., Tyrrell, A. M., Trefzer, M. A. & Lones, M., Feb 2019
Article in Biosystems

Research output: Contribution to conference › Paper › peer-review

Author(s)

Department/unit(s)

Electronic Engineering

Publication details

Date	Accepted/In press - 10 Dec 2015
Original language	English

Abstract

EpiNet is a novel computational model which is able to perform dynamic topological modification autonomously throughout execution. This approach is inspired by the functionality of eukaryotic gene regulation, specifically that of chromatin modification which is able to modify its structure dynamically, altering the structure of gene regulatory networks. In this work we utilise the dynamic properties of epiNet when applied to two different methods of edge detection, and analyse these networks and their dynamical properties via structural and dynamical
systems analysis.

Projects

Bio-inspired Adaptive Architectures and Systems
Project: Research project (funded) › Research

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By the same authors

Using Epigenetic Networks for the Analysis of Movement Associated with Levodopa Therapy for Parkinson's Disease

Evolving efficient solutions to complex problems using the Artificial Epigenetic Network

Operating Beyond FPGA Tool Limitations: Nervous Systems for Embedded Runtime Management

Embedded Social Insect-Inspired Intelligence Networks for System-level Runtime Management

Evolutionary acquisition of complex traits in artificial epigenetic networks