Alan Moses' Computational Biology Lab
Research in the Moses lab is focused on two major areas:  Regulatory networks and systems and Population genomics

To find our more about our research, please see our recent publications.

Regulatory Networks and Systems

Most biological processes are the result of many genes working together in pathways or networks. 

Our work on regulatory networks and systems aims to understand two basic questions: 1) how is gene regulation encoded in DNA and protein sequences, and 2) how does gene regulation evolve.

We use compuational methods to study these questions in a variety of organisms, including humans, flies and plants.

For example, we work on predicting DNA regulatory sequences that are important for transcription in the mouse brain (Figure 1) and predicting protein regulatory sequences that determine nuclear localization.
Gene regulation underlies many biological phenomena

forebrain predictions

Subtle changes in regulatory networks might explain why very different organisms (such as human and chimpanzee) can have very similar genes.

To study evolution of regulatory networks we quantify changes in the sequences that specify gene regulation (Figure 2), and develop mathematical modelling methods to study evolution of regulatory networks.
Figure 1. Expression of reporter constructs in mouse embryos (from Pennachio et al. 2006)

Figure 2. Quantifying rates of transcription factor binding sites turnover (from Moses et al. 2006)

Population genomics

One of our favourite model systems is yeast: it's great for making beer, bread, wine... (Figure 3). But it is also great for computational and molecular biology experiments. 

We've been studying how genetic differences in yeast are distributed in the population and we apply mathematical models of molecular evolution to predict how natural selection and genetic drift affect mutations in functional sequences. One of our favourite models that relates function to patterns of evolution is the Halpern-Bruno model (Figure 4)

Figure 3. Budding yeast.
Figure 4. Halpern-Bruno proportionality relates the probability of fixation, F, to functional parameters f, and mutation rates P

Alan Moses' Lab, Copyright 2009-2011.