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Dataset results
155 results for “Range Structure”
The impact of estimator choice: Disagreement in clustering solutions across K estimators for Bayesian analysis of population genetic structure across a wide range of empirical datasets
Open the record for dataset details and reuse information.
Individual transcription factors modulate both the micromovement of chromatin and its long-range structure [ChIP-Seq]
GEO Series GSE262601. Mus musculus. 5 samples. Type: Genome binding/occupancy profiling by high throughput sequencing.
Individual transcription factors modulate both the micromovement of chromatin and its long-range structure [RNA-Seq]
GEO Series GSE262603. Mus musculus. 4 samples. Type: Expression profiling by high throughput sequencing.
G-quadruplex structures regulate long-range transcriptional reprogramming to promote drug resistance in ovarian cancer [ATAC-seq]
GEO Series GSE279495. Homo sapiens. 8 samples. Type: Genome binding/occupancy profiling by high throughput sequencing.
G-quadruplex structures regulate long-range transcriptional reprogramming to promote drug resistance in ovarian cancer [CUT&Tag]
GEO Series GSE279641. Homo sapiens. 12 samples. Type: Genome binding/occupancy profiling by high throughput sequencing.
G-quadruplex structures regulate long-range transcriptional reprogramming to promote drug resistance in ovarian cancer [RNA-seq]
GEO Series GSE279501. Homo sapiens. 24 samples. Type: Expression profiling by high throughput sequencing.
Data from: Geographic ranges of genera and their constituent species: structure, evolutionary dynamics, and extinction resistance
We explore the relationships among the geographic ranges of genera, the ranges and positions of their constituent species, and the number of species they contain, considering variation among coeval genera and changes within genera over time. Measuring range size as the maximal distance, or extent, between occurrences within a taxon, we find that the range of the most widespread species is a good predictor of the range of the genus, and that the number of species is a better predictor still. This analysis is complicated by a forced correlation: the range of a genus must be at least as large as that of each of its constituent species. We therefore focus on a second measure of range, the mean squared distance, or dispersion, of occurrences from the geographic centroid, which, by analogy to the analysis of variance, allows the total dispersion of a genus to be compared to the mean within-species dispersion and the dispersion among species centroids. We find that among-species dispersion is the principal determinant of genus dispersion. Within-species dispersion also plays a major role. The role of species richness is relatively small. Our results are not artifacts of temporal variation in the geographic breadth of sampled data. The relationship between changes in genus dispersion and changes in within- and among-species dispersion shows a symmetry, being similar in cases when the genus range is expanding and when it is contracting. We also show that genera with greater dispersion have greater extinction resistance, but that within- and among-species dispersion are not demonstrable predictors of survival once the dispersion of the genus is accounted for. Thus it is the range of the genus, rather than how it is attained, that is most relevant to its fate. Species richness is also a clear predictor of survival, beyond its effects on geographic range.
Data from: Near infrared spectroscopy (NIRS) predicts non-structural carbohydrate concentrations in different tissue types of a broad range of tree species
1. The allocation of non-structural carbohydrates (NSCs) to reserves constitutes an important physiological mechanism associated with tree growth and survival. However, procedures for measuring NSC in plant tissue are expensive and time-consuming. Near-infrared spectroscopy (NIRS) is a high-throughput technology that has the potential to infer the concentration of organic constituents for a large number of samples in a rapid and inexpensive way based on empirical calibrations with chemical analysis. 2. The main objectives of this study were (i) to develop a general NSC concentration calibration that integrates various forms of variation such as tree species and tissue types and (ii) to identify characteristic spectral regions associated with NSC molecules. In total, 180 samples from different tree organs (root, stem, branch, leaf) belonging to 73 tree species from tropical and temperate biomes were analysed. Statistical relationships between NSC concentration and NIRS spectra were assessed using partial least squares regression (PLSR) and a variable selection procedure (competitive adaptive reweighted sampling, CARS), in order to identify key wavelengths. 3. Parsimonious and accurate calibration models were obtained for total NSC (r2 of 0·91, RMSE of 1·34% in external validation), followed by starch (r2 = 0·85 and RMSE = 1·20%) and sugars (r2 = 0·82 and RMSE = 1·10%). Key wavelengths coincided among these models and were mainly located in the 1740–1800, 2100–2300 and 2410–2490 nm spectral regions. 4. This study demonstrates the ability of general calibration model to infer NSC concentrations across species and tissue types in a rapid and cost-effective way. The estimation of NSC in plants using NIRS therefore serves as a tool for functional biodiversity research, in particular for the study of the growth–survival trade-off and its implications in response to changing environmental conditions, including growth limitation and mortality.
R unmarked dataframe: Fine-scale forest structure, not management regime, drives occupancy of a declining songbird, the Olive-sided Flycatcher, in the core of its range
<p>Encounter history, site covariates, and observation covariates formatted as an unmarkedFrameOccu object for use in program R with the package unmarked to replicate the analyses conducted by Hack et al. in 'Fine-scale forest structure, not management regime, drives occupancy of a declining songbird, the Olive-sided Flycatcher, in the core of its range.'</p>
Data from: Near infrared spectroscopy (NIRS) predicts non-structural carbohydrate concentrations in different tissue types of a broad range of tree species
Open the record for dataset details and reuse information.
Data from: Geographic ranges of genera and their constituent species: structure, evolutionary dynamics, and extinction resistance
Open the record for dataset details and reuse information.
G-quadruplex structures regulate long-range transcriptional reprogramming to promote drug resistance in ovarian cancer [ChIP-seq]
GEO Series GSE279497. Homo sapiens. 12 samples. Type: Genome binding/occupancy profiling by high throughput sequencing.
Individual transcription factors modulate both the micromovement of chromatin and its long-range structure [Hi-C]
GEO Series GSE262602. Mus musculus. 6 samples. Type: Other.
Individual transcription factors modulate both the micromovement of chromatin and its long-range structure
GEO Series GSE262605. Mus musculus. 15 samples. Type: Genome binding/occupancy profiling by high throughput sequencing; Other; Expression profiling by high throughput sequencing.
Structural elements promote architectural stripe formation and facilitate ultra-long-range gene regulation at a human disease locus
GEO Series GSE223132. Homo sapiens. 18 samples. Type: Genome binding/occupancy profiling by high throughput sequencing.
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
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.