Please use this identifier to cite or link to this item:
Full metadata record
DC FieldValueLanguage
dc.contributor.advisorAbbott, Dereken
dc.contributor.advisorAllison, Andrew Gordonen
dc.contributor.authorBerryman, Matthew Johnen
dc.description.abstractComplex systems are those which exhibit one or more of the following inter-related behaviours: 1. Nonlinear behaviour: the component parts do not act in linear ways, that is the superposition of the actions of the parts is not the output of the system. 2. Emergent behaviour: the output of the system may be inexpressible in terms of the rules or equations of the component parts. 3. Self-organisation: order appears from the chaotic interactions of individuals and the rules they obey. 4. Layers of description: in which a rule may apply at some higher levels of description but not at lower layers. 5. Adaptation: in which the environment becomes encoded in the rules governing the structure and/or behaviour of the parts (in this case strictly agents) that undergo selection in which those that are by some measure better become more numerous than those that are not as “fit”. A single cell is a complex system: we cannot explain all of its behaviour as simply the sum of its parts. Similarly, DNA structures, social networks, cancers, the brain, and living beings are intricate complex systems. This thesis tackles all of these topics from a complex systems approach. I have skirted some of the philosophical issues of complex systems and mainly focussed on appropriate tools to analyse these systems, addressing important questions such as: • What is the best way to extract information from DNA? • How can we model and analyse mutations in DNA? • Can we determine the likely spread of both viruses and ideas in social networks? • How can we model the growth of cancer? • How can we model and analyse interactions between genes in such living systems as the fruit fly, cancers, and humans? • Can complex systems techniques give us some insight into the human brain?en
dc.format.extent319443 bytesen
dc.format.extent2941665 bytesen
dc.format.extent344632 bytesen
dc.subjectcomplex systems; cancer; signal processing; metabolomics, gene regulatory networks, nonlinear dynamics, EEG, mutationen
dc.subject.lcshSignal processingen
dc.subject.lcshSystem analysis.en
dc.subject.lcshMutation (Biology)en
dc.subject.lcshGenetic regulation.en
dc.titleA complex systems approach to important biological problems.en
dc.contributor.schoolSchool of Electrical and Electronic Engineeringen
dc.provenanceCopyright material removed from digital thesis. See print copy in University of Adelaide Library for full text.en
dc.description.dissertationThesis (Ph.D.)-- School of Electrical and Electronic Engineering, 2007en
Appears in Collections:Research Theses

Files in This Item:
File Description SizeFormat 
01front.pdf336.55 kBAdobe PDFView/Open
02main.pdf2.87 MBAdobe PDFView/Open
03append-bib.pdf311.96 kBAdobe PDFView/Open

Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.