Publications
Preprints
- Annabel Large*, Ian Holmes. Nested birth-death processes are competitive with parameter-heavy neural networks as time-dependent models of protein evolution, bioRxiv 2026
Journal Articles
Svante Resjö, Jakob Willforss, Annabel Large*, Valentina Siino, Erik Alexandersson, Fredrik Levander, Erik Andreasson. Comparative proteomic analyses of potato leaves from field-grown plants grown under extremely long days, Plant Physiology and Biochemistry 2024
Priscilla Olayide, Annabel Large*, Linnea Stridh, Ismail Rabbi, Susanne Baldermann, Livia Stavolone, Erik Alexandersson. Gene Expression and Metabolite Profiling of Thirteen Nigerian Cassava Landraces to Elucidate Starch and Carotenoid Composition, Agronomy 2020
Brittni R Kelley, J Christopher Ellis, Annabel Large*, Liesel G Schneider, Daniel Jacobson, Jeremiah G Johnson. Whole-Genome Sequencing and Bioinformatic Analysis of Environmental, Agricultural, and Human Campylobacter jejuni Isolates From East Tennessee, Frontiers in Microbiology 2020
Anna Furches, David Kainer, Des Weighill, Annabel Large*, Piet Jones, Angelica M Walker, Jonathon Romero, Joao Gabriel Felipe Machado Gazolla, Wayne Joubert, Manesh Shah, Jared Streich, Priya Ranjan, Jeremy Schmutz, Avinash Sreedasyam, David Macaya-Sanz, Nan Zhao, Madhavi Z Martin, Xiaolan Rao, Richard A Dixon, Stephen DiFazio, Timothy J Tschaplinski, Jin-Gui Chen, Gerald A Tuskan, Daniel Jacobson. Finding New Cell Wall Regulatory Genes in Populus trichocarpa Using Multiple Lines of Evidence, Frontiers in Plant Science 2019
Select Presentations
- Annabel Large*, Ian Holmes. “Nested birth-death processes are competitive with parameter-heavy neural networks as time-dependent models of protein evolution”.
- Probabilistic Modeling in Genomics 2026, Berkeley, CA, USA (2026).
- Mathematical and Computational Evolutionary Biology, Heraklion, Greece (2026).
- The Annual Meeting of the Society for Molecular Biology and Evolution, Copenhagen, Denmark (2026).
- Annabel Large*, Ian Holmes. “Nested birth-death processes are competitive with parameter-heavy neural networks as time-dependent models of protein evolution”. legend2024 : Machine Learning for Evolutionary Genomics Data, Heraklion, Greece (2024).
