DocumentCode :
412550
Title :
Structure and dynamics of a gene network model incorporating small RNAs
Author :
Geard, Nicholas ; Wiles, Janet
Author_Institution :
Sch. of ITEE, Queensland Univ., Brisbane, Qld., Australia
Volume :
1
fYear :
2003
fDate :
8-12 Dec. 2003
Firstpage :
199
Abstract :
As advances in molecular biology continue to reveal additional layers of complexity in gene regulation, computational models need to incorporate additional features to explore the implications of new theories and hypotheses. It has recently been suggested that eukaryotic organisms owe their phenotypic complexity and diversity to the exploitation of small RNAs as signalling molecules. Previous models of genetic systems are, for several reasons, inadequate to investigate this theory. In this study, we present an artificial genome model of genetic regulatory networks based upon previous work by Torsten Reil, and demonstrate how this model generates networks with biologically plausible structural and dynamic properties. We also extend the model to explore the implications of incorporating regulation by small RNA molecules in a gene network. We demonstrate how, using these signals, highly connected networks can display dynamics that are more stable than expected given their level of connectivity.
Keywords :
artificial life; evolutionary computation; genetics; macromolecules; molecular biophysics; RNA molecules; artificial genome model; biological structure; computational models; connectivity level; dynamic properties; eukaryotic organisms; gene network model; gene regulation; genetic systems; molecular biology; phenotypic complexity; phenotypic diversity; signalling molecules; Bioinformatics; Biological system modeling; Biology computing; Computational biology; Computational modeling; Displays; Genetics; Genomics; Organisms; RNA;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Evolutionary Computation, 2003. CEC '03. The 2003 Congress on
Print_ISBN :
0-7803-7804-0
Type :
conf
DOI :
10.1109/CEC.2003.1299575
Filename :
1299575
Link To Document :
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