Robert Murphy Bets Self-Driving Instruments Will Crack Biology’s Mysteries

The Carnegie Mellon computational biologist thinks machine learning algorithms can direct high-throughput experiments to solve the field’s unanswered questions.

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It was the code that hooked Bob Murphy on biology. At age 13, he visited New York City’s American Museum of Natural History with his parents and picked up a copy of Isaac Asimov’s book The Genetic Code in the gift shop. After reading it, “I came downstairs, and I told my parents, ‘I know what I want to do with my life,’” he recalls. “I was just fascinated by the idea that you could decode biological information, that biological systems were built on this DNA material that could be converted into RNAs and proteins.”

That was in the mid-1960s. Murphy, true to his word, went on to study biochemistry at Columbia University. Then in 1974, when he was in graduate school at Caltech, he encountered another type of code that would shape his career. One day, after he’d extracted proteins from chromatin and run polyacrylamide gels of the samples, ...

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Meet the Author

  • Shawna Williams

    Shawna was an editor at The Scientist from 2017 through 2022. She holds a bachelor's degree in biochemistry from Colorado College and a graduate certificate and science communication from the University of California, Santa Cruz.

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May 2019 The Scientist Issue
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