Author

Oliver Pybus

Royal Veterinary College

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

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Evolutionary Biology· 2 Genetics· 1

Signature Assays, Organisms & Methods

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Approach:statistical model· 3 Research Focus:phylogenetics / evolution· 2 Organism:human· 1 Assay:whole-genome sequencing· 1

Frequent Co-Authors

Adriaan M. DokteriD· 1 shared Alexander MaksiaeviD· 1 shared Alvin Crespo-BellidoiD· 1 shared Andrew RambautiD· 1 shared Astrid GalliD· 1 shared Ethan PlunkettiD· 1 shared Gerton Lunter· 1 shared Guy BaeleiD· 1 shared

Activity by Year

2016-2026 · peak 2/yr

Co-Author Collaboration Network

10 top collaborators · 22 mutual co-author links

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1 shared paperEvolutionary Biology

Adriaan M. DokterORCID

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3 papers

Recent·Most cited

Dairy cattle movement networks govern the spread and persistence of H5N1 B3.13 in the United States

Jonathan E. Pekar, Yucai Shao, Alvin Crespo-Bellido, Prathyush Sambaturu, Guy Baele, Joel O. Wertheim, Praneeth Gangavarapu, Karthik Gangavarapu, Gytis Dudas, Thomas P. Peacock, Alexander Maksiaev, Tanin Rajamand, Michael W. Sanderson, Justin Bahl, Ethan Plunkett, , Philippe Lemey

The paper analyzes the spread of H5N1 B3.13 in U.S. dairy cattle using genomic data and movement networks, finding that cattle movement, not birds, drives the outbreak.

bioRxiv · Oct 31, 2026 · PreprintEvolutionary Biology

A phylogenetic codon substitution model for antibody lineages

Kenneth Hoehn, Gerton Lunter, Oliver Pybus

This paper develops a phylogenetic substitution model that accounts for hotspot motifs in antibody lineage evolution, showing improved fit and reduced bias in parameter estimation.

bioRxiv · May 26, 2016Evolutionary Biology

Coalescent inference using serially sampled, high-throughput sequencing data from intra-host HIV infection

Kevin Dialdestoro, Jonas Andreas Sibbesen, Lasse Maretty, Jayna Raghwani, Astrid Gall, Paul Kellam, Oliver Pybus, Jotun Hein, Paul Jenkins

This paper introduces a method to infer evolutionary dynamics of intra-host HIV using deep sequencing data, finding mutation rates and population sizes comparable to BEAST.

Genetics · Feb 5, 2016Peer-reviewedGenetics