IIUM Repository (IREP)

Developing an emergent theoretical framework for artificial pseudo-gene communication pathway in DNA computing

Shamsudin, Ahmad Faizul and Suhaimi, Mohd Adam and M., Huweldi and Seth, Salam and N., Aishah and A. F., AlyaKhadijah and R., Hidayah and Noorbatcha, Ibrahim Ali (2012) Developing an emergent theoretical framework for artificial pseudo-gene communication pathway in DNA computing. In: International Conference on Advanced Computer Science and Informations (ICACSIS 2012), 1-2 December 2012, University of Indonesia.

[img] PDF (ICACSIS 2012 Proceedings paper) - Published Version
Restricted to Registered users only

Download (451kB) | Request a copy

Abstract

The extended information theory of Shannon with Feynman used in natural DNA computing is proposed to be used for artificial pseudo-gene computing. The theory predicts the performance in terms of information decays of the pseudo-gene communication system of information encoding, transmission and decoding similar to natural molecular reactions. An emergent theoretical framework for artificial pseudo-genes using cooperative multi-agents with gene motif binary switching algorithm is developed. The results indicated differences in information decays between artificial and natural DNA computing systems. Further development of the gene motif binary switch algorithm may achieve convergence between the artificial and natural systems

Item Type: Conference or Workshop Item (Full Paper)
Additional Information: 1394/28576
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Kulliyyahs/Centres/Divisions/Institutes: Kulliyyah of Engineering > Department of Biotechnology Engineering
Kulliyyah of Information and Communication Technology
Kulliyyah of Information and Communication Technology
Depositing User: Prof. Dr. Ibrahim Ali Noorbatcha
Date Deposited: 17 Jan 2013 14:40
Last Modified: 13 Feb 2013 19:56
URI: http://irep.iium.edu.my/id/eprint/28576

Actions (login required)

View Item View Item

Downloads

Downloads per month over past year