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3,339 results for “heterogeneities”
Fast likelihood calculations for automatic identification of macroevolutionary rate heterogeneity in continuous and discrete traits
<p>Understanding phenotypic disparity across the tree of life requires identifying where and when evolutionary rates change on phylogeny. A primary methodological challenge in macroevolution is therefore to develop methods for accurate inference of among-lineage variation in rates of phenotypic evolution. Here, we describe a method for inferring among-lineage evolutionary rate heterogeneity in both continuous and discrete traits. The method assumes that the present-day distribution of a trait is shaped by a variable-rate process arising from a mixture of constant-rate processes and uses a single-pass tree traversal algorithm to estimate branch-specific evolutionary rates. By employing dynamic programming optimization techniques and approximate maximum likelihood estimators where appropriate, our method permits rapid exploration of the tempo and mode of phenotypic evolution. Simulations indicate that the method reconstructs rates of trait evolution with high accuracy. Application of the method to datasets on squamate reptile reproduction and turtle body size recovers patterns of rate heterogeneity identified by previous studies but with computational costs reduced by many orders of magnitude. Our results expand the set of tools available for detecting macroevolutionary rate heterogeneity and point to the utility of fast, approximate methods for studying large scale biodiversity dynamics.</p>
What doesn't kill you can make you stronger: variation in plasticity in response to early temporally heterogeneous hydrological experience
<p><span>Temporally heterogeneous environments may drive rapid and continuous plastic responses, leading to highly variable plasticity in traits. However, direct experimental evidence for such meta-plasticity due to environmental heterogeneity is rare.</span></p> <p><span>Our objective was to investigate the effects of early experience with temporally heterogeneous water availability on the subsequent plasticity of plant species in response to water conditions.</span></p> <p><span>We subjected</span><span> eight plant species</span><span> from three habitats</span><span>, four exotic and four native to North America,</span><span> to initial exposure to either a first round of alternating drought and inundation treatment (</span><span>E<sub>het</sub></span><span>, temporally heterogeneous experience) or a consistently moderate water supply (</span><span>E<sub>hom</sub></span><span>, homogeneous experience), and to a second round of drought, moderate watering or inundation treatments. Afterwards the performance in a series of traits of these species, after the first and second rounds of treatments, was measured. </span></p> <p><span>Compared to E<sup>hom</sup>, E<sub>het</sub> increased final mean total mass of all species considered together, but did not affect mean mortality. E<sub>het</sub> relative to E<sub>hom</sub>, decreased the initial total mass of native species as a group, but increased the mass of exotic species or species from hydric habitats; E<sub>het</sub> also increased the late growth of natives, but did not for exotics, and increased the late growth of mesic species more than xeric and hydric species.</span></p> <div> <p><span>Our results suggest that previous</span> <span>exposure to temporal heterogeneity in water supply may be not beneficial immediately, but can be beneficial for plant growth and response to water stress later in a plant's lifetime.</span> <span>Heterogeneous experiences may not necessarily enhance the degree of plasticity, but may improve the expression of plasticity in terms of better performance later,</span><span> effects of which differ for different groups of species, suggesting species-specific strategies for dealing with fluctuating abiotic environments. </span></p> <p><span><em>Synthesis</em>.</span><span> Previous </span><span>temporally heterogeneous experience can benefits plant growth later in life though modulating the expression of plasticity</span><span>, leading to adaptive meta-plasticity</span><span>. </span><span>Studies of meta-plasticity </span><span>may not only improve</span><span> our understanding of the importance of variable plasticity in relation how plants </span><span>cope with environmental challenges, but also </span><span>the costs versus benefits of plastic responses and its limits over the long term.</span></p> </div>
Data from: Mitochondrial phylogenomics of early land plants: mitigating the effects of saturation, compositional heterogeneity, and codon-usage bias
Phylogenetic analyses using concatenation of genomic-scale data have been seen as the panacea to resolving the incongruences among inferences from few or single genes. However, phylogenomics may also suffer from systematic errors, due to the, perhaps cumulative, effects of saturation, among-taxa compositional (GC content) heterogeneity, or codon-usage bias plaguing the individual nucleotide loci that are concatenated. Here we provide an example of how these factors affect the inferences of the phylogeny of early land plants based on mitochondrial genomic data. Mitochondrial sequences evolve slowly in plants and hence are thought to be suitable for resolving deep relationships. We newly assembled mitochondrial genomes from 20 bryophytes, complemented these with 40 other streptophytes (land plants plus algal outgroups), compiling a data matrix of 60 taxa and 41 mitochondrial genes. Homogeneous analyses of the concatenated nucleotide data resolve mosses as sister-group to the remaining land plants. However, the corresponding translated amino acid data support the liverwort lineage in this position. Both results receive weak to moderate support in maximum likelihood analyses, but strong support in Bayesian inferences. Tests of alternative hypotheses using either nucleotide or amino-acid data provide implicit support for the respective optimal topologies. By analyzing the nucleotide data, we found that the 3rd codon positions are more saturated than the 1st and 2nd codon positions, and excluding these from the analyses leads to a topology congruent with that obtained using amino-acid data. Further, we determined that land plant lineages differ in their nucleotide composition, and in their usage of synonymous codon variants. Composition heterogeneous Bayesian analyses employing a non-stationary model that accounts for variation in among-lineage composition, and inferences from degenerated nucleotide data that avoids the effects of synonymous mutations that underlie codon-usage bias, again recovered liverworts being sister to the remaining land plants. These analyses indicate that the discrepancy between the nucleotide-based and the amino acid-based trees is caused by the lineage specific, parallel compositional bias, or synonymous mutations driving codon-usage bias, as well as saturation in the 3rd codon positions. While genomic data may generate highly supported phylogenetic trees, these inferences may be artifacts. We suggest that phylogenomic analyses should assess the possible impact of potential biases through comparisons of protein coding gene data and their amino-acids translations, by analyzing data modeling compositional bias, and by excluding nucleotide noisy signals due to saturation or codon-usage bias. We caution against relying on any one presentation of the data (nucleotide or amino acid) or any one type of analysis even when analyzing large-scale data sets, no matter how well-supported, without fully exploring the effects of substitution models.
Data from: Ribosomal DNA sequence heterogeneity reflects intra-species phylogenies and predicts genome structure in two contrasting yeast species
The ribosomal RNA encapsulates a wealth of evolutionary information, including genetic variation that can be used to discriminate between organisms at a wide range of taxonomic levels. For example, the prokaryotic 16S rDNA sequence is very widely used both in phylogenetic studies and as a marker in metagenomic surveys and the ITS region, frequently used in plant phylogenetics, is now recognised as a fungal DNA barcode. However, this widespread use does not escape criticism, principally due to issues such as difficulties in classification of paralogous versus orthologous rDNA units and intragenomic variation, both of which may be significant barriers to accurate phylogenetic inference. We recently analysed datasets from the Saccharomyces Genome Resequencing Project, characterising rDNA sequence variation within multiple strains of the baker's yeast <i>Saccharomyces cerevisiae</i> and its nearest wild relative <i>Saccharomyces paradoxus</i> in unprecedented detail. Notably, both species possess single locus rDNA systems. Here, we use these new variation datasets to assess whether a more detailed characterisation of the rDNA locus can alleviate the second of these phylogenetic issues, sequence heterogeneity, while controlling for the first. We demonstrate that a strong phylogenetic signal exists within both datasets and illustrate how they can be used, with existing methodology, to estimate intra-species phylogenies of yeast strains consistent with those derived from whole-genome approaches. We also describe the use of partial Single Nucleotide Polymorphisms, a type of sequence variation found only in repetitive genomic regions, in identifying key evolutionary features such as genome hybridisation events and show their consistency with whole-genome Structure analyses. We conclude that our approach can transform rDNA sequence heterogeneity from a problem to a useful source of evolutionary information, enabling the estimation of highly accurate phylogenies of closely related organisms, and discuss how it could be extended to future studies of multi-locus rDNA systems.
Heterogeneous glycosylation and methylation of the Aeromonas caviae flagellin.
<p>Manual analysis of A. caviae FlaB glycopepetides</p>
Assessing methods for representing soil heterogeneity through a flexible approach within the Joint UK Land Environment Simulator (JULES) at version 3.4.1
<p>This is the JULES input and output data and plotting scripts used in the paper titled "Assessing methods for representing soil heterogeneity through a flexible approach within the Joint UK Land Environment Simulator (JULES) at version 3.4.1.</p> <p>The tar file contains the following:</p> <p>outputs/cardwfdei_gl4_uncompressed.mon.nc<br> outputs/cardwfdei_gl4_surf_ft_dom_soil.mon.nc<br> outputs/cardwfdei_gl4_gb_dom_soil_decompr_loam.mon.nc<br> outputs/cardwfdei_gl4_surf-soil_consolidated.mon.nc<br> outputs/cardwfdei_gl4_gb_dom_soil_compr_loam.mon.nc<br> plotting_scripts/utils.py<br> plotting_scripts/gb_flux_summary.py<br> plotting_scripts/tile_fsmc_summary.py<br> plotting_scripts/gb_smcl_closure_summary.py<br> plotting_scripts/colors_names.py<br> inputs/drive-file-WFDEI-79-10.txt<br> inputs/WFDEI_data/README.txt<br> inputs/extract_cardwfdei_point.py</p> <p>uncompressed is the output for experiment HResTex.<br> surf_ft_dom_soil is the output for experiment SurfDom.<br> gb_dom_soil_decompr_loam is the output for experiment SurfGB.<br> surf-soil_consolidated is the output for experiment HResTexAgg.<br> gb_dom_soil_compr_loam is the output for experiment DC.</p> <p>Descriptions about the individual plotting scripts are given within each file.</p> <p>The WFDEI data is freely available from a separate source and inputs/WFDEI_data/README.txt describes how to obtain this dataset.</p> <p>inputs/extract_cardwfdei_point.py extracts the WFDEI data for the single latitude/longitude point used in this paper.</p> <p>inputs/drive-file-WFDEI-79-10.txt is the input file required by JULES to read in the WFDEI driving data files.</p>
Datasets for "Learning Anisotropic Interaction Rules from Individual Trajectories in a Heterogeneous Cellular Population"
<p>Datasets used as examples in "<strong>Learning Anisotropic Interaction Rules from Individual Trajectories in a Heterogeneous Cellular Population</strong>", DA Messenger, GE Wheeler, X Liu DM Bortz, arXiv:2204.14141, 2022. </p> <p>Code: <a href="https://github.com/MathBioCU/WSINDy_CellCluster">https://github.com/MathBioCU/WSINDy_CellCluster</a></p> <p>Download code and run <strong>visualize_trajectories.m , </strong>changing file in line 5 accordingly.</p> <p> </p> <p> </p>
Supplemental Material: Dynamic Team Heterogeneity in Cooperative Coevolutionary Algorithms
<p>Supplemental videos for the paper "Dynamic Team Heterogeneity in Cooperative Coevolutionary Algorithms".</p> <p>multirover_720.mp4: Best solutions evolved for the multi-rover task.</p> <p>soccer_720.mp4: Best solutions evolved for the soccer task.</p>
Data From: Investigating the Effect of GLU283 Protonation State on the Conformational Heterogeneity of CCR5 by Molecular Dynamics Simulations
<p>This dataset contains MD simulation results for CCR5 receptor in different states. There are three states this GPCR could be in: 1.apo state, i.e. not bound to any other protein or ligand 2.holo state, i.e. bound by maraviroc (MRV) 3.GP120 bound state, i.e. bounded to HIV envelope protein GP120 and human receptor CD4. </p> <p>For apo state simulations, three different starting structure were used and the simulation results for them are given in three different folders named after the PDB ID of initial structures. </p> <p>One critical residue of CCR5 receptor, GLU283, was considered in two different protonation state, hence there are two folders for each studied system, GLU283 and GLH283 for differently protonated systems. </p> <p>The MD trajectories of studied systems are in dcd format and due to size issues waters, ions and membrane atoms were removed. </p> <p>For each system, three replica MD simulations were performed, hence, there are three folders with names REPLICA1, REPLICA2, REPLICA3.</p> <p> </p>
Physiological heterogeneity of the stromatolite laminae in Longmenshan, Sichuan, China
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Cancer-specific heterogeneous networks for TREE
Open the record for dataset details and reuse information.
Fig. 2 in Data storage and data re-use in taxonomy-the need for improved storage and accessibility of heterogeneous data
Fig. 2 Sch_m_ of a data packag_ in taxonomy c_nt_r_d around a sp_cim_n. This _xampl_ is from zoology, and data typ_s will obviously diff_r among taxa
Fig. 1 in Evaluating the correlation between area, environmental heterogeneity, and species richness using terrestrial isopods (Oniscidea) from the Pontine Islands (West Mediterranean)
Fig. 1 Pontine archipelago. The geographic distance between Ventotene- Santo Stefano and the remaining islands is not in scale. 1, Scoglio Ravia; 2, Scoglio di Pilato; 3, Faraglioni della Madonna; 4, Scogli della Cantina; 5, Scoglio Cappello; 6, Faraglione di Mezzogiorno; 7, Le Galere
Figure 3 from: Araújo KC, Guzzi A, Ávila RW (2018) Influence of habitat heterogeneity on anuran diversity in Restinga landscapes of the Parnaíba River delta, northeastern Brazil. ZooKeys 757: 69-83. https://doi.org/10.3897/zookeys.757.21900
Figure 3 Accumulation curve for anurans sampled in the Parnaíba River Delta, northeastern Brazil, constructed from 1000 randomizations on the order of samplings. Species estimates (Chao 1 estimator).
Figure 2 from: Araújo KC, Guzzi A, Ávila RW (2018) Influence of habitat heterogeneity on anuran diversity in Restinga landscapes of the Parnaíba River delta, northeastern Brazil. ZooKeys 757: 69-83. https://doi.org/10.3897/zookeys.757.21900
Figure 2 Abundance of anurans species obtained in Ilha Grande de Santa Isabel Island and Canárias Island, Parnaíba River Delta, Northeastern Brazil.
Figure 1 from: Araújo KC, Guzzi A, Ávila RW (2018) Influence of habitat heterogeneity on anuran diversity in Restinga landscapes of the Parnaíba River delta, northeastern Brazil. ZooKeys 757: 69-83. https://doi.org/10.3897/zookeys.757.21900
Figure 1 Map of the Environmental Protection Area of Parnaíba River Delta (shaded area), northeastern Brazil, with the location of the study area featuring six sampling points (red triangles). Key: black square, Canárias Island, state of Maranhão; black circle, Ilha Grande de Santa Isabel Island, state of Piauí.
Figure 4 from: Araújo KC, Guzzi A, Ávila RW (2018) Influence of habitat heterogeneity on anuran diversity in Restinga landscapes of the Parnaíba River delta, northeastern Brazil. ZooKeys 757: 69-83. https://doi.org/10.3897/zookeys.757.21900
Figure 4 Association between anurans' species diversity (SHANNON-WIENER diversity index) and habitat heterogeneity in the Parnaíba River Delta, Northeastern Brazil (R² = 0.9204, p-value = 0.0015). Computation of the habitat heterogeneity index is explained in Material and methods.
Fig 1 from: Joubert-Van der Merwe L, Pryke JS (2018) Is cattle grazing more important than landscape heterogeneity for grasshoppers in Afromontane grassland? Journal of Orthoptera Research 27(1): 13-21. https://doi.org/10.3897/jor.27.15027
Fig 1 Map of study sites in the KwaZulu-Natal Midlands. Abbreviations for grazing intensity: light in iMpendle Nature Reserve (square symbols), and moderate (circular symbols) or heavy (triangular symbols) in the ecological network. Abbreviations for fire regime: annual burning (AB, solid black symbols), grasslands with longer fire rotation that were recently-burned (RB, solid grey symbols) i.e. burned < 12 months prior to sampling and unburned (UB, open symbols) i.e. burned >12 months prior to sampling.
Fig 2 from: Joubert-Van der Merwe L, Pryke JS (2018) Is cattle grazing more important than landscape heterogeneity for grasshoppers in Afromontane grassland? Journal of Orthoptera Research 27(1): 13-21. https://doi.org/10.3897/jor.27.15027
Fig 2 Grasshopper species richness responds to grazing intensity under different fire regimes. Pairwise comparisons among grazing intensity classes (light, moderate and heavy) for annually-burned firebreaks and grasslands with longer fire rotations that were recently-burned i.e. <12 months prior to sampling and unburned i.e. burned >12 months prior to sampling. Bars with the same letters are not significantly different from one another.
Fig 3 from: Joubert-Van der Merwe L, Pryke JS (2018) Is cattle grazing more important than landscape heterogeneity for grasshoppers in Afromontane grassland? Journal of Orthoptera Research 27(1): 13-21. https://doi.org/10.3897/jor.27.15027
Fig 3 Canonical analysis of principal coordinates ordination (CAP) of grasshopper assemblage composition to display patterns in the data. Abbreviations for grazing intensity: light in the protected area (square symbols), and moderate (circular symbols) or heavy (triangular symbols) in the ecological network. Abbreviations for fire regime: annual burning (AB, solid black symbols), grasslands with longer fire rotation that were recently-burned (RB, solid grey symbols) i.e. burned < 12 months prior to sampling and unburned (UB, open symbols) i.e. burned >12 months prior to sampling. Significance values for pairwise comparisons are in Table 4.
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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.