Yesterday's refusal by the UK government to posthumously pardon Alan Turing makes sad news for maths, computer science and the fight against discrimination. But even if symbolic gestures are, symbolically, being rebuffed, at least Turing's most important legacy — the scientific one — is going stronger than ever. An example is this week's announcement that scientists have devised a biological computer, based on an idea first described by Turing in the 1930s.
One of the greatest advances in the biomedical sciences has been the unravelling of our genetic code. This new understanding sheds light on what makes organisms function and how they are related to each other, helps to combat diseases, and to convict criminals. But it also poses great mathematical challenges: the genetic revolution is an information explosion which can only be tamed using mathematical methods.
"It's a match!" cries the CSI. At first glance it might seem that if the police have matched a suspect's DNA to evidence from the crime scene, then the case is closed. But some statistical thinking is required to understand exactly what a match is, and importantly, how juries should assess this as part of the evidence in a trial.
The human genome is represented by a sequence of 3 billion As, Cs, Gs, and Ts. With such large numbers, sequencing the entire genome of a complex organism isn't just a challenge in biochemistry. It's a logistical nightmare, which can only be solved with clever algorithms.
Next year is a great one for biology. Not only will we celebrate 150 years since the publication of On the origin of species, but also 200 years since the birth of its author, Charles Darwin. At the heart of Darwin's theory of evolution lies a beautifully simple mathematical object: the evolutionary tree. In this article we look at how maths is used to reconstruct and understand it.