Allen Rodrigo

Group research focus

Broadly, our research focuses on the development of computational and statistical methods in evolutionary biology.  Right now, we are working on three projects. First, we are developing new methods of inferring phylogenies and evolutionary models by using next-generation sequences in more efficient ways. Our other two projects are relatively new: we are looking at evolutionary models of how microbial communities associate with hosts, and we trying to understand whether the evolutionary relationships and dynamics of tumour cells allow us to predict the health outcome of patients diagnosed with cancer. 

How did you become a computational biologist?

When I was going through my PhD back in the ‘80s, there was no discipline called “computational biology” or “bioinformatics”.  There was already a tradition of applying mathematical and numerical methods in biology, amongst ecologists, evolutionary biologists and taxonomists, but a great deal of this was done with calculus and matrices.  When computers became more commonplace, folks from a variety of disciplines – e.g., computer science, zoology, botany, linguistics – began to experiment with the use of computers to solve these problems.  I always had an interest in the intersection of mathematics, computing and evolutionary biology, so my PhD used all three to address a pretty dry taxonomic problem (revision a family of helminth parasites found in turtles – fun fact, I won the student prize at the Australian Parasitology Society Conference in 1989 held on Magnetic Island, for my presentation of this work!).  Mid-way through my PhD, PCR was invented (!), but I didn’t get to do any wet lab work until my first postdoc at the University of Auckland in 1990.  After that, I swore off lab-work (I have “bad hands”), and became a full-time computational biologist. 

What do you enjoy most about teaching?

As a quantitative biologist myself, I am an evangelist for biological numeracy.  I teach mathematical and statistical stuff to biology students who are equation-averse. Consequently, I try to expose them to as many equations as possible, so that they lose their fear of symbols. The thing I enjoy most about teaching is seeing the lights come on in people’s eyes.  The best part of teaching typically happens mid-way through a course, when students begin to understand that its not all magic and gobbledygook.