July 2010 - Swinburne University of Technology
July 2010 - Swinburne University of Technology
July 2010 - Swinburne University of Technology
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swinburne JULY <strong>2010</strong><br />
BIOMEDICINE<br />
20<br />
Mathematicians are attempting to develop algorithms to solve ‘master equations’ that could<br />
one day help biomedicine even the odds against infectious diseases BY DR GIO BRAIDOTTI<br />
INFECTIOUS-DISEASE SPECIALISTS call it<br />
the ‘Red Queen strategy’ and viruses are<br />
particularly good at it. By constantly changing<br />
their molecular identity through genetic<br />
trickery, viruses keep the immune system<br />
perpetually running after an ever-elusive<br />
opponent … much like the Red Queen’s race<br />
in Lewis Carroll’s Through the Looking-Glass,<br />
where the Red Queen and Alice run faster and<br />
faster just to remain in the same place.<br />
The human immunodeficiency virus, HIV,<br />
which is responsible for AIDS, is a master<br />
practitioner <strong>of</strong> the strategy. So is influenza.<br />
Molecular biology has developed<br />
the means to even the odds against the<br />
viruses, but to make the most <strong>of</strong> these<br />
biotechnologies there is a need to understand<br />
how infections unfold in human patients. At<br />
stake are the principles that determine how<br />
individual viruses infect, reproduce, mutate,<br />
spread – or better yet, become extinct –<br />
within diverse and unique human hosts.<br />
But while an infection’s predator/<br />
prey-like dynamics matter when designing<br />
therapeutic counter-strategies to the Red<br />
Queen, explaining these dynamics presents<br />
enormous problems to mathematicians.<br />
At <strong>Swinburne</strong> <strong>University</strong> <strong>of</strong> <strong>Technology</strong>,<br />
Pr<strong>of</strong>essor Peter Drummond and Dr Tim<br />
Vaughan from the Centre for Atom Optics<br />
and Ultrafast Spectroscopy (CAOUS) know<br />
first-hand what biomedicine researchers are<br />
up against. There are so many interacting<br />
health, lifestyle and genetic variables<br />
affecting immune systems and viruses across<br />
the human population, creating so many<br />
infection scenarios, that tracking them all is<br />
extraordinarily complex. Pr<strong>of</strong>essor Drummond<br />
says the timeframes needed to run calculations<br />
could potentially exceed the lifespan <strong>of</strong> the<br />
universe. In other words, the calculations are<br />
solvable, but not in a realistic timeframe.<br />
The complexity is not just due to the<br />
evolving, self-organising nature <strong>of</strong> living<br />
organisms. There are also reasons that relate<br />
to millennia-old mathematical conundrums<br />
posed by dynamic systems that change<br />
seemingly chaotically or unpredictably.<br />
“In natural populations humans respond<br />
to infection differently, the viral population<br />
can mutate as it increases, and this results<br />
in an astronomical number <strong>of</strong> possibilities,”<br />
Pr<strong>of</strong>essor Drummond says. “That’s what<br />
we mean by ‘computational complexity’ –<br />
situations where the number <strong>of</strong> states that a<br />
calculation needs to track is astronomically<br />
high.”<br />
While statistics has solved some issues –<br />
notably in the case <strong>of</strong> thermodynamics and<br />
quantum mechanics – Dr Vaughan wants to use<br />
new techniques never before applied to biology<br />
to efficiently solve population/infection.<br />
“Currently researchers are using<br />
supercomputers to run simulations that<br />
track every cell death and birth, in a brute<br />
force calculation,” Dr Vaughan says.<br />
“These computations are driven by the<br />
‘master equation’ – a raw mathematical<br />
description <strong>of</strong> how a probability distribution<br />
changes over time. So our goal is to find<br />
more efficient ways <strong>of</strong> solving the master<br />
equation, borrowing from techniques used in<br />
statistical physics.”<br />
To make the leap to a biological system,<br />
however, the project needs data representative