C
Chi Zhang
Researcher at Chinese Academy of Sciences
Publications - 51
Citations - 3893
Chi Zhang is an academic researcher from Chinese Academy of Sciences. The author has contributed to research in topics: Coalescent theory & Population. The author has an hindex of 15, co-authored 46 publications receiving 2252 citations. Previous affiliations of Chi Zhang include Swiss Institute of Bioinformatics & ETH Zurich.
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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.
Journal ArticleDOI
Total-Evidence Dating under the Fossilized Birth-Death Process.
Chi Zhang,Tanja Stadler,Tanja Stadler,Seraina Klopfstein,Seraina Klopfstein,Tracy A. Heath,Tracy A. Heath,Tracy A. Heath,Fredrik Ronquist +8 more
TL;DR: It is shown that the explicit modeling of fossilization and sampling processes can improve divergence time estimates, but only if all important model aspects, including sampling biases, are adequately addressed.
Journal ArticleDOI
Evaluation of a Bayesian Coalescent Method of Species Delimitation
TL;DR: The results suggest that Bayesian analysis under the multispecies coalescent model may provide important insights into population divergences, and may be useful for generating hypotheses of species delimitation, to be assessed with independent information from anatomical, behavioral, and ecological data.
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
Bayesian inference of species networks from multilocus sequence data
TL;DR: This work presents a Bayesian approach to jointly infer species networks and gene trees from multilocus sequence data, and provides an extensible framework for Bayesian inference of reticulate evolution.