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datasets available to search
ShareScore release 0.9.0
Dataset results
41 results for “Bayesian phylogenetic analysis”
Phlorest phylogeny derived from Kitchen et al. 2009 'Bayesian phylogenetic analysis of Semitic languages identifies an Early Bronze Age origin of Semitic in the Near East'
<p>Cite the source of the dataset as:</p> <blockquote> <p>Kitchen A, Ehret C, Assefa S & Mulligan CJ. 2009. Bayesian phylogenetic analysis of Semitic languages identifies an Early Bronze Age origin of Semitic in the Near East. Proceedings of the Royal Society B: Biological Sciences, 270(1668), 2703-2710.</p> </blockquote>
Phlorest phylogeny derived from Lee & Hasegawa 2011 'Bayesian phylogenetic analysis supports an agricultural origin of Japonic languages'
<p>Cite the source of the dataset as:</p> <blockquote> <p>Lee S, Hasegawa T (2011) Bayesian phylogenetic analysis supports an agricultural origin of Japonic languages. Proceedings of the Royal Society B: Biological Sciences, 278(1725):3662–9.</p> </blockquote>
CLDF dataset derived from Lee and Hasegawa's "Bayesian phylogenetic analysis supports an agricultural origin of Japonic languages" from 2011
<p>Cite the source of the dataset as:</p> <blockquote> <p>Lee, Sean and Hasegawa, Toshikazu (2011). Bayesian phylogenetic analysis supports an agricultural origin of Japonic languages. Proceedings of the Royal Society B: Biological Sciences, 278(1725), 3662–3669. doi:10.1098/rspb.2011.0518.</p> </blockquote>
Supplementary Materials to "Subgrouping in a `dialect continuum': A Bayesian phylogenetic analysis of the Mixtecan language family"
<p>SM0: metadata on the languages of the sample</p> <p>SM 1: custom word list</p> <p>SM2: prose explanation of cognate coding and IPA conversion</p> <p>SM3: annotated cognate sets</p> <p>SM4: nexus files of the broad and fine grained cognate coding</p> <p>SM5: NeighborNet visualization with coloring by Josserand (1983)'s groupings and by groupings from our analysis</p> <p>SM6: BEAST2 xml files</p> <p>SM7: MCC trees from BEAST2 analysis</p> <p>SM8: DensiTree visualization and visualization of full MCC tree of best performing model</p>
Fig. 1. Bayesian majority rule consensus tree reconstructed for 90 in Phylogenetic analysis and systematic position of two new species of the ant genus Crematogaster (Hymenoptera, Formicidae) from Southeast Asia
Fig. 1. Bayesian majority rule consensus tree reconstructed for 90 taxa using five genes (ArgK, CAD, LWRh, Top1, Wg) in a MrBayes analysis. Above node numbers indicate posterior probability. Data were partitioned by PartitionFinder v.1.1.1 and analyzed using a best fit model for each gene and codon position, with 10 million generations and a burn-in of 25 %. Area enclosed by dashed lines is enlarged on Fig. 2.
CLDF dataset derived from Kitchen et al.'s "Bayesian phylogenetic analysis of Semitic languages" from 2009
<p>Cite the source of the dataset as:</p> <blockquote> <p>Bayesian phylogenetic analysis of Semitic languages identifies an Early Bronze Age origin of Semitic in the Near East. Andrew Kitchen, Christopher Ehret, Shiferaw Assefa, Connie J. Mulligan. Proc. R. Soc. B 2009 -; DOI: 10.1098/rspb.2009.0408. Published 29 April 2009</p> </blockquote>
FIGURE 4 Phylogenetic relationships within the genus Longidorus. Bayesian 50 in Molecular phylogenetic analysis and comparative morphology reveals the diversity and distribution of needle nematodes of the genus Longidorus (Dorylaimida: Longidoridae) from Spain
FIGURE 4 Phylogenetic relationships within the genus Longidorus. Bayesian 50% majority rule consensus tree as inferred from cytochrome c oxidase subunit I (CoxI) mtDNA gene sequence alignment under the general time-reversible model of sequence evolution with correction for invariable sites and a gammashaped distribution (GTR + I + G). Posterior probabilities greater than 0.70 are given for appropriate clades. Newly obtained sequences in this study are shown in bold. Scale bar = expected changes per site.
FIGURE 3 Phylogenetic relationships within the genus Longidorus. Bayesian 50 in Molecular phylogenetic analysis and comparative morphology reveals the diversity and distribution of needle nematodes of the genus Longidorus (Dorylaimida: Longidoridae) from Spain
FIGURE 3 Phylogenetic relationships within the genus Longidorus. Bayesian 50% majority rule consensus tree as inferred from 18S rRNA gene sequence alignment under a transitional model with invariable sites and a gamma correction (TIM 2 + I + G). Posterior probabilities greater Downloaded than 0.70 from are Brill given.comfor08/29/ appropriate 2023 05:44:51PM clades. Newly obtained sequences in this study are shown in bold. Scale bar = expected changesvia per site free. access
FIGURE 1 Phylogenetic relationships within the genus Longidorus. Bayesian 50 in Molecular phylogenetic analysis and comparative morphology reveals the diversity and distribution of needle nematodes of the genus Longidorus (Dorylaimida: Longidoridae) from Spain
FIGURE 1 Phylogenetic relationships within the genus Longidorus. Bayesian 50% majority rule consensus tree as inferred from D2 and D3 expansion domains of 28S rRNA sequence alignment under an SYM model with invariable sites and a gamma-shaped distribution (SYM + I + G). Posterior probabilities greater than 0.70 are given for appropriate clades. Newly obtained sequences in this study are shown in bold. Scale bar = expected changes per site. ** = Branches collapsed, indicating clustered Longidorus species. For a more specific detail of collapsed clades, see supplementary fig. S1.
FIGURE 2 Phylogenetic relationships within the genus Longidorus. Bayesian 50 in Molecular phylogenetic analysis and comparative morphology reveals the diversity and distribution of needle nematodes of the genus Longidorus (Dorylaimida: Longidoridae) from Spain
FIGURE 2 Phylogenetic relationships within the genus Longidorus. Bayesian 50% majority rule consensus tree as inferred from ITS1 rRNA sequence alignment under a 3-parameter model with invariable sites and a gamma-shaped distribution (TPM3 µf + I + G). Posterior probabilities greater than 0.70 are given for appropriate clades. Newly obtained sequences in this study are shown in bold. Scale bar = expected changes per site. Downloaded from Brill.com08/29/2023 05:44:51PM via free access
Data and scripts for: Bayesian Phylogenetic Analysis on multi-core Compute Architectures: Implementation and evaluation of BEAGLE in RevBayes with MPI
<p>Phylogenies are central to many research areas in biology and commonly estimated using likelihood-based methods. Unfortunately, any likelihood-based method, including Bayesian inference, can be restrictively slow for large datasets–with many taxa and/or many sites in the sequence alignment–or complex substitution models. The primary limiting factor when using large datasets and/or complex models in probabilistic phylogenetic analyses is the likelihood calculation, which dominates the total computation time. To address this bottleneck, we incorporated the high-performance phylogenetic library BEAGLE into RevBayes, which enables multi-threading on multi-core CPUs and GPUs, as well as hardware-specific vectorized instructions for faster likelihood calculations. Our new implementation of RevBayes+BEAGLE retains the flexibility and dynamic nature that users expect from vanilla RevBayes. Additionally, we implemented a native parallelization within RevBayes without an external library using the message passing interface (MPI); RevBayes+MPI. We evaluated our new implementation of RevBayes+BEAGLE using multi-threading on CPUs and a powerful NVidia Titan V GPU against our native implementation of RevBayes+MPI. We found good improvements in speedup when multiple cores were used with up to 20-fold speedup when using multiple CPUs and over 90-fold speedup when using multiple GPU cores. The improvement depended on the data type used, DNA or amino acids, and the size of the alignment, but less on the size of the tree. We additionally investigated the cost of rescaling partial likelihoods to avoid numerical underflow and showed that unnecessarily frequent rescaling can increase runtimes 2.5 to 3-fold. Finally, we presented and compared a new approach to store partial likelihoods on branches instead of nodes which can speed up computations but comes at twice the memory requirements.</p> <p>Availability: The software described in the paper is available at https://github.com/revbayes/revbayes with documentation and tutorials found at https://revbayes.github.io.</p>
figure 6 Bayesian 50 in Zebrus pallaoroi sp. nov.: a new species of goby (Actinopterygii: Gobiidae) from the Mediterranean Sea with a DNA-based phylogenetic analysis of the Gobius-lineage
figure 6 Bayesian 50% majority-rule consensus tree estimation of phylogenetic relationships of analysed species from the Gobius-lineage sensu Agorreta et al. (2013) based on the nuclear gene rhodopsin. Numbers on branches are Bayesian posterior probabilities and maximum likelihood bootstrap values, respectively. Only values higher than 0.9 for posterior probability and 70% for bootstrap are shown.
figure 5 Bayesian 50 in Zebrus pallaoroi sp. nov.: a new species of goby (Actinopterygii: Gobiidae) from the Mediterranean Sea with a DNA-based phylogenetic analysis of the Gobius-lineage
figure 5 Bayesian 50% majority-rule consensus tree estimation of phylogenetic relationships of analysed species from the Gobius-lineage sensu Agorreta et al. (2013) based on the mitochondrial gene cytochrome b. Numbers on branches are Bayesian posterior probabilities and maximum likelihood bootstrap values, respectively. Only values higher than 0.9 for posterior probability and 70% for bootstrap are shown.
Data and scripts for: Bayesian Phylogenetic Analysis on multi-core Compute Architectures: Implementation and evaluation of BEAGLE in RevBayes with MPI
Open the record for dataset details and reuse information.
A Bayesian Phylogenetic Hidden Markov Model for B Cell Receptor Sequence Analysis
<p>simulation and PC64/VRC01 input/output data files</p>
FIGURE 7. Phylogenetic tree from Bayesian analysis. Thick branches indicate posterior probabilities over 80 in Revision of the Ranitomeya fantastica species complex with description of two new species from Central Peru (Anura: Dendrobatidae)
FIGURE 7. Phylogenetic tree from Bayesian analysis. Thick branches indicate posterior probabilities over 80.
FIGURE 1. Maximum clade credibility tree after a partitioned Bayesian analysis using 8945 in Phylogenetic analysis of the Neotropical Pristimantis leptolophus species group (Anura: Craugastoridae): molecular approach and description of a new polymorphic species
FIGURE 1. Maximum clade credibility tree after a partitioned Bayesian analysis using 8945 sites depicting the phylogenetic relationships among Pristimantis including the Pristimantis leptolophus species group. Numbers on nodes represent posterior probabilities and ultrafast bootstrap (as obtained in the ML analysis) support respectively. Asterisks represent nodal support larger than 95% in both ML and Bayesian analyses. Two dashes in ultrafast bootstrap indicate the node was not recovered in the ML analysis (see Appendix 2 for the ML tree).
FIGURE. (A) Summary phylogeny showing relations between genera in tribe Phyllantheae from Bayesian and Maximum Likelihood analysis of five markers (ITS, PHYC, accD–psaI, trnS–trnG, matK), modified from Appendix 1. Classification is shown of genera (right column), subgenera (middle column) and sections (except for the genus Phyllanthus. Sections not included in phylogenetic analyses and those for the genus Flueggea were omitted. (B) summary phylogeny of the genus Phyllanthus as envisioned here with subgenera and sections of groups included in phylogenetic studies shown. in A revised phylogenetic classification of tribe Phyllantheae (Phyllanthaceae)
FIGURE. (A) Summary phylogeny showing relations between genera in tribe Phyllantheae from Bayesian and Maximum Likelihood analysis of five markers (ITS, PHYC, accD–psaI, trnS–trnG, matK), modified from Appendix 1. Classification is shown of genera (right column), subgenera (middle column) and sections (except for the genus Phyllanthus. Sections not included in phylogenetic analyses and those for the genus Flueggea were omitted. (B) summary phylogeny of the genus Phyllanthus as envisioned here with subgenera and sections of groups included in phylogenetic studies shown.
FIGURE. Phylogenetic tree derived from Bayesian analysis, based on nrLSU data. Posterior probability (PP> 0.95) values from the Bayesian analysis are added at the nodes. The scale bar represents the number of nucleotide changes per site. (T) indicates the type specimen for this species. The new species are in bold. in Four new species of Entoloma (Entolomataceae, Agaricomycetes) subgenera Cyanula and Claudopus from Vietnam and their phylogenetic position
FIGURE. Phylogenetic tree derived from Bayesian analysis, based on nrLSU data. Posterior probability (PP> 0.95) values from the Bayesian analysis are added at the nodes. The scale bar represents the number of nucleotide changes per site. (T) indicates the type specimen for this species. The new species are in bold.
FIGURE. Multilocus phylogenetic tree inferred from Bayesian analysis based on the combined TEF1-α and ACT sequences. Bayesian posterior probabilities are indicated next to the nodes. The tree was rooted with Cladosporium herbarum CBS 121621. The species in this study are indicated in bold. Types of species are indicated after the culture collection number (T = ex-type, ex-epitype, ex-neotype, or reference strain). in Six new species of Cladosporium associated with decayed leaves of native bamboo (Bambusoideae) in a fragment of Brazilian Atlantic Forest
FIGURE. Multilocus phylogenetic tree inferred from Bayesian analysis based on the combined TEF1-α and ACT sequences. Bayesian posterior probabilities are indicated next to the nodes. The tree was rooted with Cladosporium herbarum CBS 121621. The species in this study are indicated in bold. Types of species are indicated after the culture collection number (T = ex-type, ex-epitype, ex-neotype, or reference strain).
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International Brain Laboratory public data
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OpenNeuro
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