Kristen Naegle

Kristen Naegle, Ph.D., is an Associate Professor in Biomedical Engineering at the University of Virginia’s School of Engineering and Applied Science, affiliated with the Center for Public Health Genomics. Her work integrates computational and experimental methods to study tyrosine phosphorylation networks in cellular signaling, focusing on their roles in cancer and other diseases. She leads the Naegle Lab, which develops tools and algorithms to advance precision medicine and systems biology.

Naegle holds a Ph.D. in Biological Engineering from MIT (2010), an S.M. in Biological Engineering from MIT (2006), and degrees in Electrical Engineering from the University of Washington (B.S., 2001; M.S., 2004). Her research bridges disciplines, combining machine learning, systems biology, and bioinformatics to decode complex cellular processes.

Her research interests include machine learning applications in biomedical data, systems biology modeling, bioinformatics tool development, and translational biotechnology. She investigates how tyrosine phosphorylation regulates cell signaling in cancer, diabetes, and inflammatory diseases, with a focus on cell context-dependent network dysregulation.

Naegle has received notable awards, including the UVA Research Achievement Award (2022) and the “Best of 2021” recognition from PLoS Computational Biology. She teaches courses such as BME 4360/6360: Molecular Data Science and BME 6xxx Research Fundamentals.

Key grants include NIH/NCI funding for developing molecular tools for tyrosine phosphorylation studies and NIH/NIGMS support for systems-level analyses of phosphorylation networks. Collaborative projects include the NIH/NCI-funded SASCO Center, investigating cancer organelle adaptations, and NIH/NAIAD-funded work on T-cell signaling in immune checkpoint therapies.

Her lab’s innovations, such as the KSTAR algorithm and CoDIAC interaction analysis tool, exemplify her commitment to translational research. Current efforts aim to enhance understanding of tyrosine phosphorylation dynamics and their clinical applications in precision oncology and cardiac therapies.