Jonathan Warrell

Jonathan Warrell is an Associate Research Scientist at the Yale School of Medicine, specializing in computational biology and interdisciplinary research at the intersection of quantum computing, machine learning, and biomedical applications. His work focuses on spatial genomics, protein phase separation modeling, and AI-driven drug discovery. Key collaborations include projects with Mark Gerstein (quantum computing), David Rimm (immunotherapy biomarkers), and Alexander Urban (single-cell genomics).

Research Interests:

• Development of quantum machine learning frameworks for drug design
• Spatially resolved transcriptomics analysis in cancer immunotherapy
• Graph-theoretical approaches to protein phase separation modeling
• Evolutionary frameworks for cultural and biological systems

Recent Work Trends: His publications (2022-2025) emphasize integration of quantum computing methods with biological data analysis, spatial multi-omics approaches for cancer research, and computational modeling of complex biological systems. Notable projects include the 388-human-brain single-cell genomics study and AI-driven T-cell receptor design for cancer therapy.

Advising & Grants: No trainees listed. Active in collaborative grant-funded projects involving Yale's Department of Genetics and Computational Biology Institute, though specific grants are not detailed in the provided text.