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242 results for “Maximum Likelihood”
Figure 3. Maximum Likelihood phylogenetic tree inferred from 695 in Genetic Relationships of Long-nosed Potoroos Potorous tridactylus (Kerr, 1792) from the Bass Strait Islands, with Notes on the Subspecies Potorous tridactylus benormi Courtney, 1963
Figure 3. Maximum Likelihood phylogenetic tree inferred from 695 bp of CO1 mtDNA sequence, including data from the Potorous tridactylus benormi Holotype (AM M.8319) and Paratype (AM M.8373). Bootstrap values for major lineages are shown. A similar tree topology was inferred from Bayesian inference.
Fig. 1. Phylogeny and habitus shots. A. Maximum Likelihood phylogeny for the genus Aname L. Koch, 1873 in Description of five new Aname L. Koch, 1873 (Araneae, Anamidae) species collected on Bush Blitz expeditions
Fig. 1. Phylogeny and habitus shots. A. Maximum Likelihood phylogeny for the genus Aname L. Koch, 1873 showing major clades and the position of new species described herein (blue taxa), support values on the phylogeny show the results of 1000 ultrafast bootstrap replicates: black circles = ≥ 95%; grey circles = 80–94%; support values less than 80% are written. Support values for some very shallow intraspecific nodes have been removed for clarity. Photos on the right (by M. Harvey) show: B. Aname ningaloo sp. nov. ♀ (WAM T148012). C. Aname salina sp. nov. ♀ (WAM T148135). D. A. salina sp. nov. ♂ (WAM T153270).
Fig. 3. Maximum likelihood tree estimated from the 215 in Morphological and Molecular Identification of Isospora sepetibensis (Chromista: Miozoa: Eimeriidae) from a New Host, Trichothraupis melanops (Passeriformes: Thraupidae: Tachyphoninae) in South America
Fig. 3. Maximum likelihood tree estimated from the 215 bp long cox1 sequences. Numbers at nodes represent bootstrap support (1,000 replicates; only values> 50% shown) for Neighbor-Joining and Maximum Likelihood, respectively. The scale-bar represents the number of nucleotide substitutions per site.
Fig. 2. Maximum likelihood tree estimated from the cox1 in Morphological and Molecular Identification of Isospora sepetibensis (Chromista: Miozoa: Eimeriidae) from a New Host, Trichothraupis melanops (Passeriformes: Thraupidae: Tachyphoninae) in South America
Fig. 2. Maximum likelihood tree estimated from the cox1 sequences. Numbers at nodes represent bootstrap support (1,000 replicates; only values> 50% shown) for Neighbor-Joining and Maximum Likelihood, respectively. The scale-bar represents the number of nucleotide substitutions per site.
Data from: Accelerating maximum likelihood phylogenetic inference via early stopping to evade (over-)optimization
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Machine learning can be as good as maximum likelihood when reconstructing phylogenetic trees and determining the best evolutionary model on four taxon alignments
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Maximum Likelihood Estimation of Closed Queueing Network Demands from Queue Length Data
<p>The data part of this release support the results presented in the paper <br /> "Maximum Likelihood Estimation of Closed Queueing Network Demands from Queue Length Data", by W. Wang and G. Casale, accepted for presentation at MAMA workshop 2015. </p> <p>When referring to the dataset or scripts please cite the paper above. </p>
Maximum Likelihood Estimation of Closed Queueing Network Demands from Queue Length Data
<p>The data part of this release support the results presented in the paper <br /> "Maximum Likelihood Estimation of Closed Queueing Network Demands from Queue Length Data", by W. Wang, G. Casale, A. Kattepur and M. Nambiar, accepted for presentation at ICPE 2016. </p> <p>When referring to the dataset or scripts please cite the paper above. </p>
Figure 2. - Bayesian (GTR+Γ+I and HKY+Γ models) and maximum likelihood 50% majority-rule consensus tree. Numbers in the nodes represent posterior probabilities (GTR+Γ+I and HKY+Γ, respectively), and bootstrap value for maximum likelihood and parsimony analyses, respectively. c1–Bragança, Pará; c2–Santa Maria do Pará, Pará; c3–National Forest of Amapá, Amapá; c4–Belém, Pará; i1–Solimões River, near Manaus, Amazonas; i2–Xingu River, Altamira, Pará; i3 and i4–Itacoatiara, Amazonas. MYBP–million years before present.
Figure 2. - Bayesian (GTR+Γ+I and HKY+Γ models) and maximum likelihood 50% majority-rule consensus tree. Numbers in the nodes represent posterior probabilities (GTR+Γ+I and HKY+Γ, respectively), and bootstrap value for maximum likelihood and parsimony analyses, respectively. c1–Bragança, Pará; c2–Santa Maria do Pará, Pará; c3–National Forest of Amapá, Amapá; c4–Belém, Pará; i1–Solimões River, near Manaus, Amazonas; i2–Xingu River, Altamira, Pará; i3 and i4–Itacoatiara, Amazonas. MYBP–million years before present.
Figure 10. - Maximum-likelihood phylogeny of Epicephala species based on sequences of the COI, ArgK and EF1α genes. Numbers above nodes are maximum-likelihood bootstrap support values based on 1,000 replications. The Japanese Epicephala species are marked in blue. Symbols right to species names donate ovipositor morphology: inverted U-shape, rounded apically; inverted V-shape, acute apically.
Figure 10. - Maximum-likelihood phylogeny of Epicephala species based on sequences of the COI, ArgK and EF1α genes. Numbers above nodes are maximum-likelihood bootstrap support values based on 1,000 replications. The Japanese Epicephala species are marked in blue. Symbols right to species names donate ovipositor morphology: inverted U-shape, rounded apically; inverted V-shape, acute apically.
Data from: The influence of the number of tree searches on maximum likelihood inference in phylogenomics
<p>Maximum likelihood (ML) phylogenetic inference is widely used in phylogenomics. As heuristic searches most likely find suboptimal trees, it is recommended to conduct multiple (e.g., ten) tree searches in phylogenetic analyses. However, beyond its positive role, how and to what extent multiple tree searches aid ML phylogenetic inference remains poorly explored. Here, we found that a random starting tree was not as effective as the BioNJ and parsimony starting trees in inferring ML gene tree and that RAxML-NG and PhyML were less sensitive to different starting trees than IQ-TREE. We then examined the effect of the number of tree searches on ML tree inference with IQ-TREE and RAxML-NG, by running 100 tree searches on 19,414 gene alignments from 15 animal, plant, and fungal phylogenomic datasets. We found that the number of tree searches substantially impacted the recovery of the best-of-100 ML gene tree topology among 100 searches for a given ML program. In addition, all of the concatenation-based trees were topologically identical if the number of tree searches was ≥ 10. Quartet-based ASTRAL trees inferred from 1 to 80 tree searches differed topologically from those inferred from 100 tree searches for 6 /15 phylogenomic datasets. Lastly, our simulations showed that gene alignments with lower difficulty scores had a higher chance of finding the best-of-100 gene tree topology and were more likely to yield the correct trees.</p>
Phylogenetic analysis of characters with dependencies under maximum likelihood
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Data from: The influence of the number of tree searches on maximum likelihood inference in phylogenomics
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Online phylogenetics using parsimony produces slightly better trees and is dramatically more efficient for large SARS-CoV-2 phylogenies than de novo and maximum-likelihood approaches
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Fig. 2 Maximum likelihood tree inferred from the combined cmdA, tef1 in New endemic Fusarium species hitch-hiking with pathogenic Fusarium strains causing Panama disease in small-holder banana plots in Indonesia
Fig. 2 Maximum likelihood tree inferred from the combined cmdA, tef1, tub, rpb1, and rpb2 sequence datasets of the Fusarium fujikuroi species complex (FFSC) including eight Indonesian isolates (indicated in blue). Bootstrap support values and Bayesian posterior probabilities are given at each node. The tree is rooted to Fusarium nirenbergiae (CBS 744.97) and F. oxysporum (CBS 716.74).
FIGURE 13. Maximum Likelihood tree inferred using the Cox1 in The identity of the invasive yellow-striped terrestrial planarian found recently in Europe: Caenoplana variegata (Fletcher & Hamilton, 1888) or Caenoplana bicolor (Graff, 1899)?
FIGURE 13. Maximum Likelihood tree inferred using the Cox1 dataset. Values at nodes correspond to BP support values (left) and PP from the Bayesian analysis (right). Vertical bars at right correspond to the molecular species delimitation methods assignations (purple: ABGD; orange: bPTP).
FIGURE5. Maximum likelihood tree based on the Kimura 2-parameter model of the COI sequences from the Siphamia species with P. kauderni as the outgroup. Tree shown here has the highest log likelihood following 10 000 replications. The percentage of trees in which the associated taxa clustered together is shown next to the branches, branch lengths are measured in the number of substitutions per site and all positions containing gaps and missing data have been eliminated. in Redescription and distributional range extension of the Speckled Siphonfish, Siphamia guttulata (Pisces: Apogonidae)
FIGURE5. Maximum likelihood tree based on the Kimura 2-parameter model of the COI sequences from the Siphamia species with P. kauderni as the outgroup. Tree shown here has the highest log likelihood following 10 000 replications. The percentage of trees in which the associated taxa clustered together is shown next to the branches, branch lengths are measured in the number of substitutions per site and all positions containing gaps and missing data have been eliminated.
FIGURE 1. Maximum likelihood tree for cytb and ITS2 in Contributions to Disholcaspis Dalla Torre And Kieffer (Hymenoptera: Cynipidae: Cynipini)
FIGURE 1. Maximum likelihood tree for cytb and ITS2, for known species of Disholcaspis and unidentified specimens. Names starting with "D_" represent specimens from Nicholls et al. (2017). Names starting with USNM are newly collected; those in blue (only) can be assigned to previously-described species based on phylogenetic placement, genetic distances, and host plant data. Bootstrap values above 50% are shown to the left of the nodes.
FIGURE 1. Maximum Likelihood tree showing phylogenetic relationships among 124 in New insights on the systematics and reproductive behaviour in tree frogs of the genus Feihyla, with description of a new related genus from Asia (Anura, Rhacophoridae)
FIGURE 1. Maximum Likelihood tree showing phylogenetic relationships among 124 representative taxa from all recognised genera of the subfamily Rhacophorinae. Relationships are inferred based on 1,937 bp of mitochondrial (12SrRNA, tRNAVAL, 16SrRNA) and nuclear (RHO and RAG1) genes. Numbers above and below the branches indicate Bayesian Posterior Probabilities and RAxML bootstrap support values, respectively.
FIGURE 1. Maximum likelihood tree generated from three mitochondrial genes shows a in Disentangling vines: a study of morphological crypsis and genetic divergence in vine snakes (Squamata: Colubridae: Ahaetulla) with the description of five new species from Peninsular India
FIGURE 1. Maximum likelihood tree generated from three mitochondrial genes shows a number of new lineages (L1–L13) identified in our study. The lineages are marked with grey bars which represent the criteria used to delimit species boundaries, where three gene bPTP (P3), genetic p-distance (GD), morphological separation (M) and geographic isolation (G) are used to predict the number of putative lineages. The nodes below 70% parametric bootstrap support are indicated with asterisk (*). "+" indicates that the status of A. nasuta cf. isabellina needs further work (see Deepak et al. 2019).
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Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
ABODe is a University of Edinburgh DataShare dataset for behavior classification in group-housed mice using home-cage video, identities, bounding boxes, ground-plate positions, and annotator labels.
DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.