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Cloud-Computing Revolution Applies to Evolution

Digital evolution.

Researchers are developing parallel-processing tools that will help track the evolution of genes and genomes across species.

Credit: ReGear Learning

Rice University researchers are using a $1.1-million U.S. National Science Foundation grant to develop parallel-processing tools that track the evolution of genes and genomes across species.

The new open source algorithms will lead to sophisticated computing techniques that can be used by researchers around the world through the cloud. The programs will be able to run parallel analyses on thousands of computers, with results that may be faster and that can trace genes on scales that were not practical before.

The project will expand upon Bayesian inference techniques that allow biologists to build on prior knowledge.

"Analyzing data sets with 10 or 20 gene sequences can easily take hundreds of hours," says Rice professor Luay Nakhleh. "But the tree of life has millions of sequences and is built from millions of species. There's no way traditional Bayesian techniques are even going to get close to handling that."

Computer farms that allow thousands of machines to cooperatively work on a problem have the potential to revolutionize bioinformatics, according to fellow Rice professor Christopher Jermaine. "We're talking about potentially taking a years- or decades-long computation and making it feasible by changing the underlying algorithm and making it amenable to distributed computing," he says.

From Rice University
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Abstracts Copyright © 2014 Information Inc., Bethesda, Maryland, USA


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