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30 results for “ancestral states”
Data from: Rate heterogeneity across Squamata, misleading ancestral state reconstruction and the importance of proper null model specification
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Reconstructing Ecological Niche Evolution via Ancestral State Reconstruction with Uncertainty Incorporated
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Ancestral state reconstruction for regeneration and autotomy in arthopods and reptiles
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Modeling pulsed evolution and time-independent variation improves the confidence level of ancestral and hidden state predictions
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Data from: Ancestral state reconstruction sheds new light on the loss of divarication hypothesis on New Zealand’s outlying islands
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Data from: Predicting the ancestral character changes in a tree is typically easier than predicting the root state
Predicting the ancestral sequences of a group of homologous sequences related by a phylogenetic tree has been the subject of many studies, and numerous methods have been proposed for this purpose. Theoretical results are available that show that when the substitution rate become too large, reconstructing the ancestral state at the tree root is no longer feasible. Here, we also study the reconstruction of the ancestral changes that occurred along the tree edges. We show that, depending on the tree and branch length distribution, reconstructing these changes (i.e. reconstructing the ancestral state of all internal nodes in the tree) may be easier or harder than reconstructing the ancestral root state. However, results from information theory indicate that for the standard Yule tree, the task of reconstructing internal node states remains feasible, even for very high substitution rates. Moreover, computer simulations demonstrate that for more complex trees and scenarios, this result still holds. For a large variety of counting, parsimony-based and likelihood-based methods, the predictive accuracy of a randomly selected internal node in the tree is indeed much higher than the accuracy of the same method when applied to the tree root. Moreover, parsimony- and likelihood-based methods appear to be remarkably robust to sampling bias and model mis-specification.
Data from: Ancestral state reconstruction, rate heterogeneity, and the evolution of reptile viviparity
Virtually all models for reconstructing ancestral states for discrete characters make the crucial assumption that the trait of interest evolves at a uniform rate across the entire tree. Although methods for identifying evolutionary rate shifts in continuous characters have attracted recent attention (e.g. Eastman et al., 2011, Stack et al., 2011), such methods for discrete characters have only very recently been developed (Beaulieu et al., 2013, Beaulieu and O'Meara 2014) and have yet to be widely used. However, ancestral state reconstructions of discrete characters are being performed on increasingly large phylogenies, where it is likely that evolutionary rates will vary greatly between different clades (Beaulieu and O'Meara 2014). Here, we show how failure to account for such variable evolutionary rates can cause highly anomalous (and likely incorrect) results, while three methods that accommodate rate variability yield the opposite, more plausible, and more robust reconstructions. The random local clock method, implemented in BEAST, estimates the position and magnitude of rate changes on the tree, split BiSSE estimates separate rate parameters for pre-specified clades, and the hidden rates model partitions each character state into a number of rate categories. The importance of accounting for rate heterogeneity in ancestral state reconstruction is highlighted empirically with a new analysis of the evolution of viviparity in squamate reptiles. Additionally, simulations show the inadequacy of traditional models when characters evolve with both asymmetry (different rates of change between states within a character) and heterotachy (different rates of character evolution across different clades).
Data from: Ancestral state reconstruction, rate heterogeneity, and the evolution of reptile viviparity
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Data from: Predicting the ancestral character changes in a tree is typically easier than predicting the root state
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Figure 1 in The tight genome size of ants: diversity and evolution under ancestral state reconstruction and base composition
Figure 1. Fluorescence intensity histograms obtained from three different species, with Drosophila melanogaster as internal standard, stained with propidium iodide (PI; A–C) or 4,6-diamidino-2-phenylindole (DAPI; D–F). The x-axis corresponds to the scale of fluorescence intensity, and the y-axis represents the number of nuclei with that fluorescence intensity.
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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.