INTELLIGENT computer programs are beginning to make discoveries of their own,
as well as saving valuable research time. Stephen Muggleton, a computer
scientist at the University of York, has been working with molecular biologists
at the Imperial Cancer Research Fund to automate protein analysis. Last week,
the team reported two discoveries: a previously unknown cancer-causing chemical
and new rules governing the three-dimensional topology of protein
structures.
Using a technique called inductive logic programming, they created an AI
system capable of making predictions based on the knowledge supplied by the
biologists and on rules learnt from the system’s “experience”. The techniques
could also have a huge role to play in the future of scientific research: “The
algorithm is producing results in a matter of minutes rather than years. AI is
going to have a significant impact on the drugs industry and the way we do
science in general,” says Muggleton.
The Brighton conference also heard that the University of Edinburgh has used
a similar program, called HR, to make mathematical findings. Last month, HR
“discovered” a new sequence of integers, called refactorables. The sequence has
been accepted into the Encyclopaedia of Online Sequences, the main global
repository for such information, the researchers say.
Toby Walsh, a member of the Edinburgh team, says HR’s intelligence comprises
a set of heuristics, or human rules of thumb. “The heuristics are sufficiently
strong that we don’t need to do too much brute-force searching,” he says. Both
Muggleton and Walsh are quick to point out that scientists should not hang up
their lab coats. “What we’re doing will help mathematicians understand how they
do mathematics, so they may be able to do it better,” says Walsh.
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When the human genome project is finished, we will have a complete map of the
gene sequence. “But,” says Muggleton, “we won’t know what it all means. The
tools we’re developing are interface techniques for dealing with this data
swamp.”
