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3,105
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3,105 results for “Vegetation =”
Vegetally localised Vrtn functions as a novel repressor to modulate bmp2b transcription during dorsoventral patterning in zebrafish
GEO Series GSE103090. Danio rerio. 2 samples. Type: Expression profiling by high throughput sequencing.
The VviNAC33 acts a molecular switch by activating leaf degreening and repressing vegetative growth during the immature-to-mature phase transition in grapevine
GEO Series GSE155445. Vitis vinifera. 2 samples. Type: Genome binding/occupancy profiling by high throughput sequencing.
Single-nucleus RNA-seq reveals that MBD5, MBD6, and SILENZIO maintain silencing in the vegetative cell of developing pollen
GEO Series GSE202422. Arabidopsis thaliana. 103 samples. Type: Expression profiling by high throughput sequencing.
Divergent Patterns of Endogenous Small RNA Populations From Seed and Vegetative Tissues of Glycine max
GEO Series GSE36728. Glycine max. 4 samples. Type: Non-coding RNA profiling by high throughput sequencing.
Control of maize vegetative and reproductive development, fertility and rRNAs silencing by HISTONE DEACETYLASE 108
GEO Series GSE101943. Zea mays. 6 samples. Type: Expression profiling by high throughput sequencing.
Untimely expression of gametogenic genes in vegetative cells causes uniparental disomy (ChIP-chip)
GEO Series GSE77015. Schizosaccharomyces pombe. 19 samples. Type: Genome binding/occupancy profiling by genome tiling array.
RNA-Seq analysis of localization along animal-vegetal axis of Xenopus laevis
GEO Series GSE104848. Xenopus laevis. 15 samples. Type: Expression profiling by high throughput sequencing.
Roles of DEMETER in regulating DNA methylation in vegetative tissues and pathogen resistance (RNA-Seq)
GEO Series GSE164915. Arabidopsis thaliana. 12 samples. Type: Expression profiling by high throughput sequencing.
Combinatorial activities of SHORT VEGETATIVE PHASE and FLOWERING LOCUS C define distinct modes of flowering regulation in Arabidopsis
GEO Series GSE54881. Arabidopsis thaliana. 18 samples. Type: Genome binding/occupancy profiling by high throughput sequencing.
Rel2-mediated transcriptional repression regulates vegetative and reproductive architecture in maize
GEO Series GSE115498. Zea mays. 6 samples. Type: Expression profiling by high throughput sequencing.
Figure 2 from: Iosypenko OO, Kyslychenko VS, Omelchenko ZI, Burlaka IS (2019) Fatty acid composition of vegetable marrows and zucchini leaves. Pharmacia 66(4): 201-207. https://doi.org/10.3897/pharmacia.66.e37893
Figure 2 Scheme of chromatography of fatty acid composition of yellow zucchini leaves.
Figure 3 from: Iosypenko OO, Kyslychenko VS, Omelchenko ZI, Burlaka IS (2019) Fatty acid composition of vegetable marrows and zucchini leaves. Pharmacia 66(4): 201-207. https://doi.org/10.3897/pharmacia.66.e37893
Figure 3 Scheme of chromatography of fatty acid composition of green zucchini leaves.
Figure 1 from: Iosypenko OO, Kyslychenko VS, Omelchenko ZI, Burlaka IS (2019) Fatty acid composition of vegetable marrows and zucchini leaves. Pharmacia 66(4): 201-207. https://doi.org/10.3897/pharmacia.66.e37893
Figure 1 Scheme of chromatography of fatty acid composition of vegetable marrows leaves.
Rangeland Analysis Platform - vegetation cover 1984
<p>Rangeland Analysis Platform vegetation cover 1984</p> <p>These data represent rangeland cover estimates determined by Jones et al. (2018)<br> and as accessible on the Rangeland Analysis Platform (https://rangelands.app).<br> Values are percent aerial cover of the following rangeland functional groups:</p> <p>Band 1 - annual forbs and grasses<br> Band 2 - bare ground<br> Band 3 - litter<br> Band 4 - perennial forbs and grasses<br> Band 5 - shrubs<br> Band 6 - trees<br> No Data value = 255</p> <p>Although these data were produced across a broad region, they are primarily<br> intended for rangeland ecosystems. Cover estimates may not be suitable in other<br> ecosystems, e.g., forests, agricultural lands.</p> <p>Data are in WGS84 Geographic Coordinate System (EPSG:4326); spatial resolution<br> is approximately 30m.</p> <p>Please attribute these data to:<br> Jones, M. O., B. W. Allred, D. E. Naugle, J. D. Maestas, P. Donnelly, L. J.<br> Metz, J. Karl, R. Smith, B. Bestelmeyer, C. Boyd, J. D. Kerby, and J. D. McIver.<br> 2018. Innovation in rangeland monitoring: annual, 30 m, plant functional type<br> percent cover maps for U.S. rangelands, 1984-2017. Ecosphere 9:e02430.<br> http://dx.doi.org/10.1002/ecs2.2430</p>
Rangeland Analysis Platform - vegetation cover 1987
<p>Rangeland Analysis Platform vegetation cover 1987</p> <p>These data represent rangeland cover estimates determined by Jones et al. (2018)<br> and as accessible on the Rangeland Analysis Platform (https://rangelands.app).<br> Values are percent aerial cover of the following rangeland functional groups:</p> <p>Band 1 - annual forbs and grasses<br> Band 2 - bare ground<br> Band 3 - litter<br> Band 4 - perennial forbs and grasses<br> Band 5 - shrubs<br> Band 6 - trees<br> No Data value = 255</p> <p>Although these data were produced across a broad region, they are primarily<br> intended for rangeland ecosystems. Cover estimates may not be suitable in other<br> ecosystems, e.g., forests, agricultural lands.</p> <p>Data are in WGS84 Geographic Coordinate System (EPSG:4326); spatial resolution<br> is approximately 30m.</p> <p>Please attribute these data to:<br> Jones, M. O., B. W. Allred, D. E. Naugle, J. D. Maestas, P. Donnelly, L. J.<br> Metz, J. Karl, R. Smith, B. Bestelmeyer, C. Boyd, J. D. Kerby, and J. D. McIver.<br> 2018. Innovation in rangeland monitoring: annual, 30 m, plant functional type<br> percent cover maps for U.S. rangelands, 1984-2017. Ecosphere 9:e02430.<br> http://dx.doi.org/10.1002/ecs2.2430</p>
Rangeland Analysis Platform - vegetation cover 1992
<p>Rangeland Analysis Platform vegetation cover 1992</p> <p>These data represent rangeland cover estimates determined by Jones et al. (2018)<br> and as accessible on the Rangeland Analysis Platform (https://rangelands.app).<br> Values are percent aerial cover of the following rangeland functional groups:</p> <p>Band 1 - annual forbs and grasses<br> Band 2 - bare ground<br> Band 3 - litter<br> Band 4 - perennial forbs and grasses<br> Band 5 - shrubs<br> Band 6 - trees<br> No Data value = 255</p> <p>Although these data were produced across a broad region, they are primarily<br> intended for rangeland ecosystems. Cover estimates may not be suitable in other<br> ecosystems, e.g., forests, agricultural lands.</p> <p>Data are in WGS84 Geographic Coordinate System (EPSG:4326); spatial resolution<br> is approximately 30m.</p> <p>Please attribute these data to:<br> Jones, M. O., B. W. Allred, D. E. Naugle, J. D. Maestas, P. Donnelly, L. J.<br> Metz, J. Karl, R. Smith, B. Bestelmeyer, C. Boyd, J. D. Kerby, and J. D. McIver.<br> 2018. Innovation in rangeland monitoring: annual, 30 m, plant functional type<br> percent cover maps for U.S. rangelands, 1984-2017. Ecosphere 9:e02430.<br> http://dx.doi.org/10.1002/ecs2.2430</p>
Rangeland Analysis Platform - vegetation cover 1989
<p>Rangeland Analysis Platform vegetation cover 1989</p> <p>These data represent rangeland cover estimates determined by Jones et al. (2018)<br> and as accessible on the Rangeland Analysis Platform (https://rangelands.app).<br> Values are percent aerial cover of the following rangeland functional groups:</p> <p>Band 1 - annual forbs and grasses<br> Band 2 - bare ground<br> Band 3 - litter<br> Band 4 - perennial forbs and grasses<br> Band 5 - shrubs<br> Band 6 - trees<br> No Data value = 255</p> <p>Although these data were produced across a broad region, they are primarily<br> intended for rangeland ecosystems. Cover estimates may not be suitable in other<br> ecosystems, e.g., forests, agricultural lands.</p> <p>Data are in WGS84 Geographic Coordinate System (EPSG:4326); spatial resolution<br> is approximately 30m.</p> <p>Please attribute these data to:<br> Jones, M. O., B. W. Allred, D. E. Naugle, J. D. Maestas, P. Donnelly, L. J.<br> Metz, J. Karl, R. Smith, B. Bestelmeyer, C. Boyd, J. D. Kerby, and J. D. McIver.<br> 2018. Innovation in rangeland monitoring: annual, 30 m, plant functional type<br> percent cover maps for U.S. rangelands, 1984-2017. Ecosphere 9:e02430.<br> http://dx.doi.org/10.1002/ecs2.2430</p>
Rangeland Analysis Platform - vegetation cover 1993
<p>Rangeland Analysis Platform vegetation cover 1993</p> <p>These data represent rangeland cover estimates determined by Jones et al. (2018)<br> and as accessible on the Rangeland Analysis Platform (https://rangelands.app).<br> Values are percent aerial cover of the following rangeland functional groups:</p> <p>Band 1 - annual forbs and grasses<br> Band 2 - bare ground<br> Band 3 - litter<br> Band 4 - perennial forbs and grasses<br> Band 5 - shrubs<br> Band 6 - trees<br> No Data value = 255</p> <p>Although these data were produced across a broad region, they are primarily<br> intended for rangeland ecosystems. Cover estimates may not be suitable in other<br> ecosystems, e.g., forests, agricultural lands.</p> <p>Data are in WGS84 Geographic Coordinate System (EPSG:4326); spatial resolution<br> is approximately 30m.</p> <p>Please attribute these data to:<br> Jones, M. O., B. W. Allred, D. E. Naugle, J. D. Maestas, P. Donnelly, L. J.<br> Metz, J. Karl, R. Smith, B. Bestelmeyer, C. Boyd, J. D. Kerby, and J. D. McIver.<br> 2018. Innovation in rangeland monitoring: annual, 30 m, plant functional type<br> percent cover maps for U.S. rangelands, 1984-2017. Ecosphere 9:e02430.<br> http://dx.doi.org/10.1002/ecs2.2430</p>
Rangeland Analysis Platform - vegetation cover 1996
<p>Rangeland Analysis Platform vegetation cover 1996</p> <p>These data represent rangeland cover estimates determined by Jones et al. (2018)<br> and as accessible on the Rangeland Analysis Platform (https://rangelands.app).<br> Values are percent aerial cover of the following rangeland functional groups:</p> <p>Band 1 - annual forbs and grasses<br> Band 2 - bare ground<br> Band 3 - litter<br> Band 4 - perennial forbs and grasses<br> Band 5 - shrubs<br> Band 6 - trees<br> No Data value = 255</p> <p>Although these data were produced across a broad region, they are primarily<br> intended for rangeland ecosystems. Cover estimates may not be suitable in other<br> ecosystems, e.g., forests, agricultural lands.</p> <p>Data are in WGS84 Geographic Coordinate System (EPSG:4326); spatial resolution<br> is approximately 30m.</p> <p>Please attribute these data to:<br> Jones, M. O., B. W. Allred, D. E. Naugle, J. D. Maestas, P. Donnelly, L. J.<br> Metz, J. Karl, R. Smith, B. Bestelmeyer, C. Boyd, J. D. Kerby, and J. D. McIver.<br> 2018. Innovation in rangeland monitoring: annual, 30 m, plant functional type<br> percent cover maps for U.S. rangelands, 1984-2017. Ecosphere 9:e02430.<br> http://dx.doi.org/10.1002/ecs2.2430</p>
Rangeland Analysis Platform - vegetation cover 1997
<p>Rangeland Analysis Platform vegetation cover 1997</p> <p>These data represent rangeland cover estimates determined by Jones et al. (2018)<br> and as accessible on the Rangeland Analysis Platform (https://rangelands.app).<br> Values are percent aerial cover of the following rangeland functional groups:</p> <p>Band 1 - annual forbs and grasses<br> Band 2 - bare ground<br> Band 3 - litter<br> Band 4 - perennial forbs and grasses<br> Band 5 - shrubs<br> Band 6 - trees<br> No Data value = 255</p> <p>Although these data were produced across a broad region, they are primarily<br> intended for rangeland ecosystems. Cover estimates may not be suitable in other<br> ecosystems, e.g., forests, agricultural lands.</p> <p>Data are in WGS84 Geographic Coordinate System (EPSG:4326); spatial resolution<br> is approximately 30m.</p> <p>Please attribute these data to:<br> Jones, M. O., B. W. Allred, D. E. Naugle, J. D. Maestas, P. Donnelly, L. J.<br> Metz, J. Karl, R. Smith, B. Bestelmeyer, C. Boyd, J. D. Kerby, and J. D. McIver.<br> 2018. Innovation in rangeland monitoring: annual, 30 m, plant functional type<br> percent cover maps for U.S. rangelands, 1984-2017. Ecosphere 9:e02430.<br> http://dx.doi.org/10.1002/ecs2.2430</p>
ScienceDex guides
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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)
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DANDI Archive for NWB datasets
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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.