A
Alex Popinga
Researcher at University of Auckland
Publications - 10
Citations - 2425
Alex Popinga is an academic researcher from University of Auckland. The author has contributed to research in topics: Coalescent theory & Bayesian inference. The author has an hindex of 5, co-authored 10 publications receiving 1300 citations. Previous affiliations of Alex Popinga include École Polytechnique Fédérale de Lausanne.
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Journal ArticleDOI
BEAST 2.5: An advanced software platform for Bayesian evolutionary analysis.
Remco R. Bouckaert,Remco R. Bouckaert,Timothy G. Vaughan,Timothy G. Vaughan,Joëlle Barido-Sottani,Joëlle Barido-Sottani,Sebastián Duchêne,Mathieu Fourment,Alexandra Gavryushkina,Joseph Heled,Graham Jones,Denise Kühnert,Nicola De Maio,Michael Matschiner,Fábio K. Mendes,Nicola F. Müller,Nicola F. Müller,Huw A. Ogilvie,Louis du Plessis,Alex Popinga,Andrew Rambaut,David A. Rasmussen,Igor Siveroni,Marc A. Suchard,Chieh-Hsi Wu,Dong Xie,Chi Zhang,Tanja Stadler,Tanja Stadler,Alexei J. Drummond +29 more
TL;DR: A series of major new developments in the BEAST 2 core platform and model hierarchy that have occurred since the first release of the software, culminating in the recent 2.5 release are described.
Posted ContentDOI
BEAST 2.5: An Advanced Software Platform for Bayesian Evolutionary Analysis
Remco R. Bouckaert,Timothy G. Vaughan,Joëlle Barido-Sottani,Sebastián Duchêne,Mathieu Fourment,Alexandra Gavryushkina,Joseph Heled,Graham Jones,Denise Kühnert,Nicola De Maio,Michael Matschiner,Fábio K. Mendes,Nicola F. Müller,Huw A. Ogilvie,Louis du Plessis,Alex Popinga,Andrew Rambaut,David A. Rasmussen,Igor Siveroni,Marc A. Suchard,Chieh-Hsi Wu,Dong Xie,Chi Zhang,Tanja Stadler,Alexei J. Drummond +24 more
TL;DR: The full range of new tools and models available on the BEAST 2.5 platform are described, which expand joint evolutionary inference in many new directions, especially for joint inference over multiple data types, non-tree models and complex phylodynamics.
Journal ArticleDOI
Efficient Bayesian inference under the structured coalescent
TL;DR: The usefulness of this new MCMC sampler is demonstrated by using it to infer migration rates and effective population sizes of H3N2 influenza between New Zealand, New York and Hong Kong from publicly available hemagglutinin gene sequences under the structured coalescent.
Journal ArticleDOI
Inferring Epidemiological Dynamics with Bayesian Coalescent Inference: The Merits of Deterministic and Stochastic Models
Alex Popinga,Timothy G. Vaughan,Timothy G. Vaughan,Tanja Stadler,Tanja Stadler,Alexei J. Drummond +5 more
TL;DR: Stochastic and deterministic coalescent susceptible–infected–removed (SIR) tree priors are developed in a Bayesian phylogenetic inference framework to permit joint estimation of SIR epidemic parameters and the sample genealogy and it is found that the stochastic variant generally outperforms its deterministic counterpart in terms of error, bias, and highest posterior density coverage.
Journal ArticleDOI
Mitogenomic diversity in Sacred Ibis Mummies sheds light on early Egyptian practices
Sally Wasef,Sally Wasef,Sankar Subramanian,Richard O'Rorke,Leon Huynen,Samia El-Marghani,Caitlin Curtis,Alex Popinga,Barbara R. Holland,Salima Ikram,Salima Ikram,Craig D. Millar,Eske Willerslev,Eske Willerslev,Eske Willerslev,David M. Lambert +15 more
TL;DR: The first study of complete mitochondrial genomes of 14 Sacred Ibis mummies interred ~2500 years ago is reported, and the ancient birds show a high level of genetic variation comparable to that identified in modern African populations, contrary to the suggestion in ancient hieroglyphics of centralized industrial scale farming of sacrificed birds.