Below are a couple of areas that my research is
currently focused on. For more detailed information about specific
projects related to these research topics please contact me directly.
Virus Evolution
An area that I have published in for the last few years is developing
and testing software and probabilistic models to understand virus
evolution. Most of these models have been assessed through
computationally-intensive Bayesian statistical methods such Markov
chain Monte Carlo. I would like to continue research in this area, with
a particular focus on full genome analyses and scaling software up to
much larger data sets. There are a number of important open questions
both on the computer science and biology sides of this research.
Genome evolution
A primary area I would like to target in the future is
empirically-driven research into evolutionary models of genomic
variation within and between species. In particular I would like to
bring genomic data to bear on current statistical models of sequence
evolution and population genetics. Initially I would like to focus on
bacterial genomes because of their relatively small size (~million
bytes) and the large numbers of publicly available genomes that have
already been sequenced to date. Of particular interest is the rapid and
accurate
in silico discovery
of short evolutionarily-related sequence fragments within and between
whole genomes.
Model comparison, model averaging and model selection
I am interested in the development of general software tools for doing
model comparison, model averaging and model selection. In particular
I am interested in models of sequence evolution and coalescent-based
models of population genetics. In this context Bayesian inference
(reversible-jump MCMC) and maximum-likelihood-based model comparison
strategies such as
AIC are both promising avenues of enquiry.
Bioinformatic software development
Through industry connections with
Biomatters
Ltd, I am interested in the development of high-level software
platforms for bioinformatic research. These interests include:
- Graphical workflow tools for bioinformatics
- High-quality libraries of bioinformatic algorithms
- Development of a bioinformatics scripting language
- Peer-to-peer collaboration tools for sharing bioinformatic data
and analyses
- High-quality visualisation tools for bioinformatic data and
analyse results
- Parallelisation and Grid-enabling of MCMC software
Funding for PhD and MSc projects in these areas is available through
the BEST scholarship program run by Biomatters.
Simulation Models of Prebiotic Evolution of Genetic
Coding
Common to all life on Earth are the mechanisms of genetic encoding, in
which specific trinucleotide sequences in DNA and RNA map to specific
amino acids in synthesized proteins.
Sidney
Markowitz's thesis project investigates feasible models of the
evolution of genetic encoding from an initially random population of
genomes and proteins. The focus of the research is on developing an
abstract framework that does not make explicit the molecular details of
replication or translation while demonstrating a plausible mechanism of
self-organisation.
Last modified: January 9, 2007
