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A Guggenheim for Warnow

A Guggenheim for Warnow

Tandy Warnow, professor of computer science at The University of Texas at Austin, has been awarded a Guggenheim fellowship for developing algorithms that enable an accounting of 3.5 billion years of evolutionary relationships.

With help from the Guggenheim, Warnow plans to take a year away from her normal academic routine. Her goal is simple: She wants to continue to improve her algorithms for estimating the evolutionary relationships between species. They are already among the best in the world—capable of sifting through galaxies of genetic data in tiny amounts of time—but she wants them to be better. And to do that, she has to go wherever in the world the brightest minds are working with the freshest data.

“Sure, you can always read what someone publishes online,” says Warnow, “but if you really want to be intimately involved in the problem, you need to be there when it is developing, when the data are being generated. You need to be with the people who understand it most deeply, and have them explain to you what they are seeing, what they are experiencing, what their impressions are. There is no online subtitute for that.”

In pursuit of improvement, Warnow will go to Switzerland to meet with the minds there who are working on improving methods in phylogenetic estimation, an area in which Warnow has been a pioneer. She’ll go to research institutes in Maryland and Massachusetts to delve into metagenomics, a field that arose when new gene sequencing technologies, combined with the kinds of analytical methods Warnow has been essential in developing, made it possible to extract meaningful genetic data from the complex soup of environmental samples.

She’ll spend a big chunk of time in Lausanne, Switzerland, where she’ll temporarily join the lab of her longtime collaborator, Bernard Moret. The two of them will work on the broad spectrum of problems, and hope that advances in one area will drive development in the others.

What’s most important, says Warnow, is simply the opportunity to shake things up, recharge her batteries, and spend time as a student rather than as a teacher or a lab supervisor.

“Maybe I’ll get lucky,” she says, “and get some breakthroughs very quickly, but that’s  not the goal. The goal is to start learning while I’m on this leave. It’s a learning phase.”
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Monday, 06 July 2020

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