Bio

Dr. Jeffrey Thorne is Professor Emeritus of Biological Sciences and Statistics at North Carolina State University, where he was a core contributor to the Bioinformatics graduate curriculum, regularly teaching Bioinformatics II (ST590C). Born in Evanston, Illinois in 1963, he studied Mathematics and Molecular Biology at the University of Wisconsin before pursuing graduate work in Genetics at the University of Washington and Cornell University.

Dr. Thorne’s research sits at the intersection of statistics, evolutionary biology, and molecular science — think of it as using the molecular “fossil record” written in DNA and protein sequences to reconstruct the deep history of life. His work focuses on evolutionary inference from interspecific data and its reconciliation with population genetics, the development of statistical tools for studying molecular evolution, protein structure and evolution, and the use of molecular and fossil data to estimate divergence times between species.

Publications

• A deep-learning-based score to evaluate multiple sequence alignments , bioRxiv (Cold Spring Harbor Laboratory) (2026)
• Using drift coefficients as a basis for inferring times, effective population sizes, and genetic adaptations , Molecular Biology and Evolution (2026)
• Likelihood-based evaluation of character recoding schemes for phylogenetic analysis , bioRxiv (Cold Spring Harbor Laboratory) (2025)
• Interlocus Gene Conversion, Natural Selection, and Paralog Homogenization , Molecular Biology and Evolution (2023)
• Scalable Bayesian Divergence Time Estimation With Ratio Transformations , Systematic Biology (2023)
• Convergent evolution of polyploid genomes from across the eukaryotic tree of life , G3 Genes Genomes Genetics (2022)
• Correlations between alignment gaps and nucleotide substitution or amino acid replacement , Proceedings of the National Academy of Sciences (2022)
• Exome sequencing of hepatocellular carcinoma in lemurs identifies potential cancer drivers , Evolution Medicine and Public Health (2022)
• Measuring Phylogenetic Information of Incomplete Sequence Data , Systematic Biology (2021)
• Pedigree-based and phylogenetic methods support surprising patterns of mutation rate and spectrum in the gray mouse lemur , Heredity (2021)

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