After an update to its software, a robot scientist has recycled its previous research to make a new biological discovery.

Named Adam, the van-sized robot came to scientific fame after autonomously investigating gene function in yeast. Those findings anticipated an era when computers wouldn't just be research tools, but researchers.

For its latest feat, described April 13 in the Journal of the Royal Society Interface, Adam revisited its original work after receiving new information about yeast growth rates. Thus refreshed, it found that crippling some enzymes could make yeast grow faster.

The findings contradict current models of yeast growth. More fundamentally, they demonstrate how to produce data for optimal use by robot scientists like Adam.

“The biology is interesting, but how the data was reused to answer new questions is what really excites me,” said computer scientist and biologist Ross King of Aberystwyth University in Wales, who led Adam's development.

While computers have been ubiquitous in research for decades, Adam and Eve, its newer King-designed companion, are two of only a handful of machines able to use artificial intelligence do science. They suggest hypotheses, design experiments, carry them out and analyze the data.

In 2009, Adam discovered the genes responsible for “orphaned” yeast enzymes, the origins of which were previously unknown. All of the data Adam generated, as well as the steps it took to arrive at its conclusions, were neatly curated and stored for future investigations.

The original data's carefully crafted representation – with everything from words like "trial" and "experiment" to protocols and results translated into computer language – was the key to Adam's new discovery, King explained.

The latest work will in turn be reused. And to make all research useful, the language of science needs to be simplified and formalized, said King. By standardizing the meanings, symbols, results and data organization used in studies, King thinks science could become a more-efficient, machine-readable enterprise.

“All scientific knowledge stands on the shoulders of giants. What we’re arguing is to make doing that a bit easier by formalizing the language and reporting of science,” he said. “Unlike the typical human approach, where what we’ve done is often not clear even to ourselves, we’d make everything explicit. It goes a long way in removing ambiguity and the need to redo experiments.”

'We probably shouldn’t try to standardize everything, or we'd see the extinction of ideas.'Computational biologist Andrey Rzhetsky of the University of Illinois, who wasn’t involved in the work, was impressed by Adam's new study.

“It’s a big deal that it can not only do science, but reuse its prior work almost automatically," said Rzhetsky. However, he struck a cautionary note about data formalization.

While it could be valuable, converting the rules of even a single field may impossible. “The real world is always changing. If you try to capture and make a permanent vision of the world, it won’t work. The standards will have to change,” Rzhetsky said.

Eliminating the diversity of language used in science may also lead to larger problems. “Different protocols and systems and languages are the essence of scientific innovation. When everyone speaks the same language, that’s bad,” Rzhetsky said. “It’s like when you lose genetic variability, you see extinction. We probably shouldn’t try to standardize everything or we’d see the extinction of ideas.”

The debate over standardizing science will continue as artificial intelligence continues to improve. In the meantime, King’s team is preparing to publish recent work completed by the newer robot Eve, which is studying drugs used to treat malaria, Chagas disease and other neglected tropical scourges.

That publication, however, is being delayed by issues beyond the ken of artificially intelligent scientists.

“We don’t want it to be exploited for profit by others,” King said. “At this point, the intellectual property issues are holding us up.”

Image: Foreground, Ross King, leader of the team that created Adam, stands in front of the robot. (Aberystwyth University)

See Also:

*Citations:

"On the formalization and reuse of scientific research." Ross D. King, Maria Liakata, Chuan Lu, Stephen G. Oliver and Larisa N. Soldatova. Journal of the Royal Society Interface. Published online April 13, 2011. DOI: 10.1098/​rsif.2011.0029

"The Automation of Science." Ross D. King, Jem Rowland, Stephen G. Oliver, Michael Young, Wayne Aubrey, Emma Byrne, Maria Liakata, Magdalena Markham, Pinar Pir, Larisa N. Soldatova, Andrew Sparkes, Kenneth E. Whelan and Amanda Clare. Science. April 3, 2009, Vol. 324, No. 5923, Pp. 85-89. DOI: 10.1126/science.1165620 *