Computational Biology
 
Evolution of Species In this area I am building on from the research in my book, with particular emphasis on the new mutation model that covers nonlinear mutation rates and various degrees of penalty on reversals, as well as studying various migration scenarios in more detail, especially those corresponding to the recent fossil Hominin discoveries of Orrorin tugenensis, Sahelanthropus tchadensis, and most recently Homo floriensis. These subjects were part of the latest developments in my model, and thus are only briefly covered in the book.

I am also extending the morphological character model in the species simulation to include composite characters, with varying degrees of significance of mutational changes. This kind of work has major implications for phylogenetic reconstruction, and my hope is that its study will lead to the discovery of more robust techniques for differentiating hereditary and non-hereditary influences on morphology. (See my developmental biology plans below for more on this point.)

I am also currently implementing a more sophisticated hybridisation model, to better study the impact of lineage merging on phylogenies and their reconstruction.

Simulating Genealogies Again building on from the research in my book, there are many interesting areas to which I am applying the simulation in order to study the complex interplay of migration, selection and demography. The book only briefly covers this area by necessity – it is just too large! Recent areas of interest are used to identify and justify particular scenarios.

I am also working on including more genes in the population simulation, to enable better simulation of linkage disequilibrium, recombination, mismatch distributions and site-frequency spectra (in similar contexts to the above). These are important for inferring population histories from genetic data, and also for questions of the location and relationships of genes along a chromosome.

Simulating Developmental Biology I have begun some preliminary investigations into simulation of the development of adult forms from the dynamic interaction of development, function and evolution. Specifically, I plan to model the development process in important morphological subsystems – e.g. masticatory, locomotor, body proportions, plus the brain, and study techniques for identifying functional parallelisms and convergences, and isolating any underlying evolutionary relatedness.

References
  • K.P. Wessen, Simulating Human Origins and Evolution, Cambridge University Press, Cambridge, 2005
  • J.Felsenstein, Inferring Phylogenies, Sinauer Associates, Sunderland, MA, 2004.
  • M. Nordborg, Coalescent theory, in D. Balding, M. Bishop and C. Canning, eds, ‘Handbook of Statistical Genetics’, Wiley, Chichester (UK), chapter 7, 2001.
  • M. Nordborg and S Tavare, Linkage disequilibrium: What history has to tell us, Trends in Genetics 18, 83–90, 2002.
  • C. Oxnard, Morphometrics of the primate skeleton and the functional and developmental underpinnings of species diversity, in P. O’Higgins and M. Cohn, eds, ‘Development, growth and evolution: Implications for the study of the hominoid skeleton’, number 20 in ‘Linnean Society Symposium Series’, Academic Press, London, chapter 10, pp. 235–263, 2000.
  • S. Kumar and P.J. Bentley (eds), On Growth, Form and Computers, Academic Press, London, 2003.

Artificial Intelligence
 
Quantitative Finance In my Quantitative Finance work, I am mostly focussed on time series related research – both high frequency and inter-day, using genetic algorithms applied to neural networks. Also, I have been investigating various aspects of the minority game, both as a market model, and as an agent-based paradigm for studying these kind of problems.

Biological Learning

In the course of the above study, I have come across some very interesting papers where the focus is not so much on building networks to solve particular problems, but rather building networks that correspond more closely with specific biological mechanisms and using them as a model for true biological learning. This appears to be a somewhat new and quite interesting area, and I expect to direct my research efforts more in this direction as time goes on.

References
  • L.J.Fogel, Intelligence Through Simulated Evolution, Wiley, New York, 1999
  • M.M. Dacorogna, R. Gençay, U.A. Müller, R.B. Olsen, and O.V. Pictet, An Introduction to High-Frequency Finance, Academic Press, San Diego, 2001
  • See various papers archived at http://www.unifr.ch/econophysics, such as P. Jeffries, N.F. Johnson, M. Hart and P.M. Hui, From market games to real-world markets, Eur. J. Phys. B, 2001 (preprint: cond-mat/0008387), and P. Jeffries and N.F. Johnson, Designing agent-based market models (preprint: cond-mat/0207523) .
  • P. Bak and D.R. Chialvo, Adaptive learning by extremal dynamics and negative feedback, Phys. Rev. E 63, 2001.

Colour Image Processing
 
Feature Detection and Segmentation

I remain very interested in image processing, especially its application to biological problems. Possible areas of study include automated biomedical image analysis – such as image enhancement and image segmentation, especially involving colour. This relates closely to work I carried out in a biomedical context while a Research Fellow in Computer Science at UWA (see this brief description). I have recently come across some research where people are treating colour images holistically using quarternions, and constructing higher dimensional analogues of convolution, correlation and Fourier transforms. This work looks very interesting, and I would like to try extending some of the Local Energy ideas that were used a lot by the UWA Computer Vision group while I was there to this problem. I have no idea at this stage of how successful this is likely to be, but is a project I would like to devote some time to investigating.

References
  • M.C. Morrone and R.A. Owens, Feature detection from local energy, Pattern Recognition Letters, 6:303-313, 1987.
  • S.J. Sangwine and T.A. Ell, Hypercomplex Fourier Transforms of Color Images, IEEE International Conference on Image Processing (ICIP 2001), Thessaloniki, Greece, 7-10 Oct. 2001, Vol. 1, pages 137-140.