Daniel Schaffer sees endless possibilities in the genomes of living organisms.

The junior in Carnegie Mellon University's Computational Biology Department is identifying regulatory elements in a genome that help determine a species' brain size relative to its body. He is part of a team looking at more than 100,000 candidates across hundreds of species for clues.

"There are so much data, so many species, so many cells, so many proteins. There are a lot of open questions that now feel so approachable," Schaffer said. "I hope to shed some light on a series of small mysteries, such as why certain people develop certain cancers or why cells express certain proteins in different ways."

Schaffer recently received a boost for shedding that light when he was named one of CMU's three 2022 Goldwater Scholars. Awarded by the federally endowed Barry Goldwater Scholarship and Excellence in Education Foundation, the scholarship provides up to $7,500 per academic year for tuition, fees, books, and room and board. It is the most prestigious STEM scholarship for undergraduates.

Schaffer's interest in computational biology started in middle school, when a passionate science teacher encouraged his early interest in the subject. While in high school, he spent three summers at the National Institutes of Health, where he pursued research that was the first to systematically analyze a large number of proteins involved in intracellular calcium storage across the entire eukaryotic lineage. The study was eventually published in Frontiers in Genetics, earning Schaffer a first-author publication as a first-year undergraduate.

The opportunity to continue to do research as an undergrad enticed Schaffer to CMU, where he's a member of Andreas Pfenning's Neurogenomics Laboratory and is mentored by Lane Postdoctoral Fellow Irene Kaplow. The team is part of the Zoonomia Consortium studying mammalian evolution, and they are building a set of computational and genomic tools to study how genome sequence influences neural cells, neural circuits, disease and behavior. One paper they co-authored was accepted last month for publication in BMC Genomics.

This coming summer, Schaffer will work with Noam Auslander at the Wistar Institute in Philadelphia. Auslander is developing machine learning methods to understand cancer evolution and unveil vulnerabilities that can be therapeutically targeted. Schaffer first met Auslander while they were both at the NIH.

"I'm excited for the opportunity to see if cancer research is something I want to do," Schaffer said. "I don't have one long-term target problem picked out yet."