By Lydia Krasilnikova ’14, MEng ’16
With the advent of DNA sequencing and other techniques, computational biologist Bonnie Berger is using computer science and mathematics to tease insights from a deluge of biological information. The theme of her work, she says, is “data, data, data.”
Professor Bonnie Berger has always had a knack for learning languages. Growing up in Miami, she could understand and speak Spanish and also studied Hebrew, becoming fluent after spending just over three months in Israel. She can read and write—and, to some extent, converse—in Russian after only two years of studying it in college. And “I always spoke math and computer science,” says Berger, SM ’86, PhD ’90, who is the Simons Professor of Mathematics, holds a joint appointment in the Department of Electrical Engineering and Computer Science, and leads the Computation and Biology group at the Computer Science and AI Lab (CSAIL). Today, she’s fluent in genomic data on top of it all. “I’m good at languages, so the language of biology was something I could pick up as well,” she says.
Berger has adapted the page-rank algorithm used by search engines to predict inherited similarities across species. She has used code-breaking strategies to predict protein structures and applied computational techniques to drug discovery. She has used language models to assess how readily SARS-CoV-2 variants will evade the immune system and employed topology to predict virus assembly and misassembly.
Berger’s research spans at least 10 different subfields, including comparative genomics, algorithms, bioinformatics, cryptography, population genetics, protein and RNA structure, drug target interactions, cancer research, virology, and one or two of her own invention. Her publication record in each one would be sufficient for an impressive career. Making an impact in so many diverse areas is extraordinary. But the way Berger sees it, she has simply gravitated to where the interesting problems are. She thinks of the result as “hybrid disciplines coming together to inform each other.”
Berger says she is driven by curiosity: “I only work on what gets me excited.” Inspired by connections between different areas, she sees their converging paths and draws from each of their toolboxes. “It’s not so much about making a career as it is about focusing on the work,” she says. “And the work is more meaningful and on target because it’s influenced by different perspectives.”
Read the full article on MIT Technology Review