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ShareScore release 0.9.0
Dataset results
109 results for “peach”
Transcriptional regulatory networks controlling woolliness in peach in response to gibberellin application and cold storage
GEO Series GSE71460. Prunus persica. 12 samples. Type: Expression profiling by array.
Identification of miRNAs and Their Target Genes in Peach (Prunus persica L.) Using High-Throughput Sequencing and Degradome Analysis
GEO Series GSE49579. Prunus persica. 4 samples. Type: Non-coding RNA profiling by high throughput sequencing; Other.
Transcriptomic analysis of peaches and nectarines reveals alternative mechanism for trichome formation
GEO Series GSE291534. Prunus persica. 20 samples. Type: Expression profiling by high throughput sequencing.
Absence of major epigenetic and transcriptomic changes accompanying the interspecific cross between peach and almond
GEO Series GSE198152. Prunus persica; Prunus dulcis; Prunus persica x Prunus dulcis. 15 samples. Type: Expression profiling by high throughput sequencing; Methylation profiling by high throughput sequencing.
VIROME OF PEACH TREES IDENTIFIED BY SMALL RNA HTS IN HUNGARY
GEO Series GSE130859. Prunus persica. 5 samples. Type: Non-coding RNA profiling by high throughput sequencing.
Unique expression, processing regulation, and regulatory network of peach (Prunus persica) miRNAs
GEO Series GSE38535. Prunus persica. 5 samples. Type: Non-coding RNA profiling by high throughput sequencing.
An integrated peach genome structural variation map uncovers genes associated with fruit traits
<p>The VCF files generated from 336 peach accessions, including SVs (>50bp), SNPs and indels (<50bp).</p>
Platform for Economic Analysis of Climate Hazards (PEACH): Gridded Hazards from 2000-2019
<p>A (quasi) global gridded hazard and socioeconomic exposure database, spanning 2000 to 2019, covering 14 climate impact drivers (CIDs) and 3 geophysical hazards.</p> <p>The Platform for Economic Analysis of Climate Hazards (PEACH) provides monthly data at an approximate 10 × 10 km resolution, with full coverage between 2004 and 2015. Unlike event-based datasets, PEACH avoids rigid inclusion thresholds whenever possible, enabling flexible definition of “extreme events” and analysis across the full hazard intensity spectrum. Six complementary socioeconomic and environmental variables are included: population, nighttime light, relative wealth, critical infrastructure, vegetation indices, and land use.</p> <p><strong>If you use PEACH in your work, please cite the paper:</strong><br>R. Reinhardt (2025) <em>The Platform for Economic Analysis of Climate Hazards (PEACH): Gridded Hazards from 2000-2019, </em> CES Working Paper, Université Paris 1 Panthéon-Sorbonne <a href="https://shs.hal.science/halshs-05314666v1" target="_blank" rel="noopener">⟨halshs-05314666⟩</a></p> <p><strong>Data Description</strong><br>The main dataset is provided in Apache Arrow Feather format, partitioned into world subregions based on the UN M49 classification. Each file contains monthly hazard exposure and socioeconomic variables per 10 km grid cell. Variable definitions, formats, and usage notes are detailed in the accompanying README.</p> <p>For ease of use, see also the <em>ConversionScript.zip</em> files, which include exemplary code for loading the data in R and Python.</p> <p><strong>Overview</strong></p> <ul> <li><strong>Temporal resolution:</strong> Monthly (2000–2019; full coverage 2004–2015)</li> <li><strong>Spatial resolution:</strong> 10 × 10 km grid cells (global coverage, rainfall quasi-global: 50°N–50°S)</li> <li><strong>Projection:</strong> EPSG:4326 (WGS 84, standard Mercator)</li> <li><strong>File format:</strong> Apache Arrow Feather (.feather), partitioned by UN M49 subregions</li> <li><strong>Hazards included:</strong></li> <ul> <li><em>Climate impact drivers (14):</em> mean air temperature, cold spells, extreme heat, mean precipitation, heavy precipitation, floods (river/pluvial), landslides, drought, fire weather & wildfires, severe windstorms, tropical cyclones, sand and dust environments (proxy indicator, not direct dust storm records), hail, air pollution (PM2.5/PM10).</li> <li><em>Geophysical hazards (3):</em> earthquakes, volcanic eruptions, tsunamis</li> </ul> </ul> <p> </p> <p><strong>Access information:</strong></p> <p><em>Access to the PEACH dataset is granted upon request for non-commercial academic and policy research. Requests will be processed as timely as possible, typically within a few business days.</em></p>
PEACH Questionnaire Study
ClinicalTrials.gov study NCT05125601. IPD Sharing: NO. Countries: 1. Publications: 0.
To Assess Bioequivalence of Loratadine Oral Solution/Syrup Versus Claritin Peach Syrup
ClinicalTrials.gov study NCT02593747. IPD Sharing: Not stated. Countries: 1. Publications: 0.
PEACH TRIAL- Precision Medicine and Adoptive Cellular Therapy
ClinicalTrials.gov study NCT04837547. IPD Sharing: NO. Countries: 1. Publications: 0.
Efficacy Evaluation of Blood Peach Extract and Rose Apple Extract on Skin
ClinicalTrials.gov study NCT06854419. IPD Sharing: NO. Countries: 1. Publications: 0.
Evaluation of Sensitization to Peach and/or Cypress in Potato Sensitized Patients in a Large Cohort
ClinicalTrials.gov study NCT05119478. IPD Sharing: UNDECIDED. Countries: 1. Publications: 0.
Increased levels of IAA are required for system 2 ethylene synthesis causing fruit softening in peach (Prunus persica (L). Batsch)
GEO Series GSE45490. Prunus persica. 9 samples. Type: Expression profiling by array.
Transcriptomic analysis reveals cold responsive genes implicated in peach low temperature tolerance
GEO Series GSE18280. Prunus persica. 4 samples. Type: Expression profiling by array.
The identification of known and novel microRNAs and their targets in peach (Prunus persica) fruit by high-throughput sequencing
GEO Series GSE83110. Prunus persica. 2 samples. Type: Other; Non-coding RNA profiling by high throughput sequencing.
RNAseq for peach weeping and standard lateral shoot (branch) tips
GEO Series GSE112080. Prunus persica. 8 samples. Type: Expression profiling by high throughput sequencing.
Chromatin and transcription dynamics regulate flower development during chilling accumulation in peach buds
GEO Series GSE190586. Prunus persica. 15 samples. Type: Genome binding/occupancy profiling by high throughput sequencing.
In depth sequencing of the siRNAs associated with peach latent mosaic viroid infection
GEO Series GSE18764. Prunus persica; Prunus persica var. nucipersica. 2 samples. Type: Non-coding RNA profiling by high throughput sequencing.
Peaches By Claude Monet
<u>Source</u>: Flickr <br><u>4DCity URL</u>: <a href="https://4dcity.org/imgupload/1677501999.1345.jpg">https://4dcity.org/imgupload/1677501999.1345.jpg</a> <br><u>Original Image URL</u>: <a href="https://live.staticflickr.com/65535/52627495110_8cb3e90dfa_m.jpg">https://live.staticflickr.com/65535/52627495110_8cb3e90dfa_m.jpg</a>
ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research 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.