StarBEAST2 statistics

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Associated diseases

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StarBEAST2 specifications

Information


Unique identifier OMICS_17202
Name StarBEAST2
Software type Package/Module
Interface Command line interface
Restrictions to use None
Operating system Unix/Linux
Programming languages Java
License GNU Lesser General Public License version 2.1
Computer skills Advanced
Version 0.14.0
Stability Stable
Maintained Yes

Subtool


  • FBD-MSC (Fossilized Birth-Death and MultiSpec

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Documentation


Maintainer


  • person_outline Huw Ogilvie <>

Publications for StarBEAST2

StarBEAST2 in publications

 (3)
PMCID: 5756848
PMID: 29321854
DOI: 10.1002/ece3.3640

[…] mcmc was run for 108generations, with one tree sampled every 1,000 generations., to obtain more accurate divergence times for macaronesian lineages, we used the coalescent species tree method starbeast2 in beast v2.4.6 (drummond et al., ). these analyses were conducted for (1) azorina, c. jacobaea and c. bravensis, (2) musschia, and (3) w. lobelioides subsp. lobelioides. we used two […]

PMCID: 5689491
PMID: 29177033
DOI: 10.1002/ece3.3261

[…] pofad (joly & bruneau, ) using the genpofad algorithm (joly, bryant, & lockhart, )., to estimate the relationship among discovered bus, we constructed a lineage tree (=species tree) in the starbeast2 (bouckaert et al., ; ogilvie, bouckaert & drummond, ) using a yule prior with a constant population model. to estimate divergence times, we used an uncorrelated log‐linear clock model […]

PMCID: 5580384
PMID: 28875076
DOI: 10.7717/peerj.3724

[…] present study does this and revises the taxonomy for two species from northern australia, carlia johnstonei and c. triacantha. we introduce an approach that is based on the recently published method starbeast2, which uses multilocus data to explore the support for alternative species delimitation hypotheses using bayes factors (bfd). we apply this method, jointly with two other multispecies […]


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StarBEAST2 institution(s)
Division of Ecology and Evolution, Research School of Biology, Australian National University, Canberra, Australia; Centre for Computational Evolution, University of Auckland, Auckland, New Zealand; Computational Evolution Group, Department of Biosystems Science and Engineering, ETH Zürich, Basel, Switzerland; Swiss Institute of Bioinformatics, Lausanne, Switzerland; School of Biological Sciences, University of Auckland, Auckland, New Zealand; Department of the Geophysical Sciences, University of Chicago, Chicago, IL, USA; Department of Computer Science, University of Auckland, Auckland, New Zealand
StarBEAST2 funding source(s)
Supported by a Royal Society of New Zealand Marsden award (16-UOA-277); by an Australian Laureate Fellowship awarded by the Australian Research Council (FL110100104); by the European Research Council under the Seventh Framework Programme of the European Commission (PhyPD: grant agreement number 335529).

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