Collegium de Lyon
France
fellow
John Huelsenbeck
2025-2026
Home institution
University of California, Berkeley
Country of origin (home institution)
United States
Discipline(s)
Biology
Theme(s)
Environment, Sustainability & Biodiversity
Fellowship dates
›
Biography
John Huelsenbeck, a native Southern Californian, studied paleontology as an undergraduate, receiving his B.A. in paleontology from the University of California, Berkeley, in 1988. He went on to study Geology at the University of Texas, Austin, but became interested in molecular evolution and, specifically, in the phylogeny problem — how can one estimate the relationships among a group of species? He graduated with a Ph.D. in Zoology in 1995. After tenure track positions at the University of Rochester and the University of California, San Diego, he started his current position at the University of California, Berkeley, as a professor in 2006. He is a charter member of the Center of Theoretical Evolutionary Genomics at UCB.
Research Project
Developing Event-Based Models to Understand the Evolution of Language and DNA
Evolutionary biologists can learn about the pattern and process of molecular evolution by comparing DNA sequences sampled from different species. However, one known process — the insertion and deletion of DNA in a sequence — has defied rigorous statistical analysis because the computations required to carry out a rigorous analysis are so expensive. The reason: The probability calculations basic to any statistical analysis account for the infinite possible ways one sequence can evolve into another. In this project, Huelsenbeck intends to condition probability calculations on a “known” history of change, thereby making probability calculations trivial. He will use a method called Markov chain Monte Carlo to numerically explore alternative histories of insertion and deletion thereby accounting for uncertainty in the histories of change. In this way, he will be able to test ideas about the process of insertion and deletion. He will extend the methodology to understand the dynamics of human language evolution.
Research Interests:
Molecular Evolution; Bayesian Statistics; Markov chain Monte Carlo