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613
datasets available to search
ShareScore release 0.9.0
Dataset results
613 results for “stress analysis”
Transcriptomic analysis of sulfur dioxide stress-resistant Saccharomyces cerevisiae strain obtained by evolutionary engineering
GEO Series GSE292349. Saccharomyces cerevisiae. 6 samples. Type: Expression profiling by array.
RNA-seq analysis of broiler liver transcriptome reveals novel responses to heat stress
GEO Series GSE51035. Gallus gallus. 8 samples. Type: Expression profiling by high throughput sequencing.
Transcriptome analysis revealed the genes involved in cold stress during flowering from Prunus sibirica
GEO Series GSE204685. Prunus sibirica. 30 samples. Type: Expression profiling by high throughput sequencing.
Comparative analysis of cotton small RNAs in response to salt stress
GEO Series GSE69702. Gossypium hirsutum. 3 samples. Type: Non-coding RNA profiling by high throughput sequencing.
RNA-seq analysis of gene expression after exposure to hot and cold stress in WT cells of Thermosynechococcus elongatus, BP-1
GEO Series GSE70086. Thermosynechococcus vestitus BP-1. 39 samples. Type: Expression profiling by high throughput sequencing.
Next generation sequencing based transcriptomic analysis of bile stress response in Lactobacillus salivarius Ren
GEO Series GSE68033. Ligilactobacillus salivarius str. Ren. 2 samples. Type: Expression profiling by high throughput sequencing.
RNA-Seq analysis of PuCH35 overexpression line and wildtype Populus ussuriensis root tips in response to PEG stress
GEO Series GSE193772. Populus ussuriensis. 12 samples. Type: Expression profiling by high throughput sequencing.
Transcriptomic analysis of tomato plants subjected to multifactorial stress combination
GEO Series GSE245759. Solanum lycopersicum. 24 samples. Type: Expression profiling by high throughput sequencing.
Global expression analysis of differential expression of genes working under Soil Water Stress condition in different genotypes of rice in Vegetative and Grain-filling stage [set 1]
GEO Series GSE49364. Oryza sativa. 12 samples. Type: Expression profiling by array.
Transcriptome Analysis of Populus x canadensis in Response to Drought Stress
GEO Series GSE64044. Populus x canadensis. 12 samples. Type: Expression profiling by high throughput sequencing.
Analysis of changes in the BLA and vmPFC brain region of control mice and global cerebral ischemia mice after acute stress
GEO Series GSE248200. Mus musculus. 6 samples. Type: Expression profiling by high throughput sequencing.
Transcription analysis of GW and SFZ lychees under lychee downy blight stress
GEO Series GSE262200. Litchi chinensis. 12 samples. Type: Expression profiling by high throughput sequencing.
Multi-omics analysis of green lineage osmotic stress pathways unveils crucial roles of different cellular compartments
GEO Series GSE260814. Chlamydomonas reinhardtii. 45 samples. Type: Expression profiling by high throughput sequencing.
Transcriptome analysis to study expression under desiccation stress of Salmonella enterica subsp. enterica serovar Agona str. 460004 2-1 on low moisture food (cereal)
GEO Series GSE297918. Salmonella enterica subsp. enterica serovar Agona. 19 samples. Type: Expression profiling by high throughput sequencing.
Response of Chinese fir Seedlings to Low Phosphorus Stress and Analysis of Gene Expression Differences
GEO Series GSE113410. Cunninghamia lanceolata. 2 samples. Type: Expression profiling by high throughput sequencing.
Comparative transcriptome analysis of manganese transportation in different leaves in soybean under manganese stress
GEO Series GSE118649. Glycine max. 12 samples. Type: Expression profiling by high throughput sequencing.
Global expression analysis of differential expression of genes working under Soil Water Stress condition in different genotypes of rice in Vegetative and Grain-filling stage [set 2]
GEO Series GSE63718. Oryza sativa. 12 samples. Type: Expression profiling by array.
Fracture Dataset accompanying the manuscript 'Stress and Rock Failure Near Salt Bodies: Insights from Field Observations, Kinematic Modeling, and Mechanical Analysis in the Paradox Basin'
<p>This data repository supports the manuscript titled <em>"Stress and Rock Failure Near Salt Bodies: Insights from Field Observations, Kinematic Modeling, and Mechanical Analysis in the Paradox Basin,"</em> submitted to the <em>Journal of Geophysical Research: Solid Earth</em>. It contains comprehensive fracture data with location coordinates referenced in the NAD83 UTM Zone 12N system. Orientation data is reported as dip and dip azimuth, and each data point is clearly labeled to indicate whether it was derived from field measurements or point cloud analyses.</p>
Dataset from the article "A comparative analysis between two flax varieties indicates lignan-mediated salt stress adaptiveness"
<p>This is a collection of raw data of the independent variables from the original research article “A comparative analysis between two flax varieties indicates lignan-mediated salt stress adaptiveness”.</p> <p> </p> <p>The file contents and descriptions are as follows:</p> <ol> <li>Biochemical Data.xlsx. This file contains the data of SOD, CAT, APX, GPOX, ROS, MDA, Proline, DPPH antioxidants, polyphenols, and phenolic acid assays.</li> <li>Genomic Data.xlsx. This file contains the Cq values of Cyklophilin, ETIF5A, microRNA 168a, microRNA 399g, and microRNA 828a obtained using the two-tailed qPCR assay.</li> <li>Morphological Data.xlsx. This file contains data on shoot-root length, root diameter, root volume, root branching, shoot-root weight, leaf count, and leaf relative water content assays.</li> </ol> <p> </p>
Data from: High-resolution methylome analysis uncovers stress-responsive genomic hotspots and drought-sensitive TE superfamilies in the clonal Lombardy poplar
<p>The following dataset contains the processed data presented in the article<strong> "High-resolution methylome analysis uncovers stress-responsive genomic hotspots and drought-sensitive TE superfamilies in the clonal Lombardy poplar"</strong></p> <ul> <li><strong>Supplementary_methods.docx: </strong>contain detailed information for the experimental stress treatments, sequencing library preparation, sequencing and DMR calling.</li> </ul> <ul> <li><strong>BedGraph files (CpG.bed, CHG.bed, CHH.bed):</strong> contain methylation levels (%) for each cytosine in the Lombardy poplar genome, in the respective sequence context. The first three columns represent the genomic coordinates of the cytosine, the 56 following columns indicate the methylation levels for each of the samples. Missing values are represented with NA (when particular cytosines were not captured by the sequencing method). </li> <li><strong>DMR_annotation_Populus_nigra_Italica_after_biotic_and_abiotic_treatments.txt: </strong>contains all the identified regions that showed significant stress-induced differential methylation (DMR). The file include all annotation for each single DMR: genomic location, genomic feature, gene, TE, sequence context and stress treatment, besides other specific relevant information.</li> <li><strong>sample_IDs_basic_metadata.txt</strong>: contains the sample ID and the associated metadata (stress treatment and ortet location and ID) for all samples used in the analysis.</li> <li><strong>Supplementary_file_1_metadata_samples.xlsx: </strong>contains the metadata associated to each sample including: sequencing statistics before and after quality and adapter trimming, read mapping and coverage statistics, and number of interrogated cytosines on each sequence context (CpG, CHG, CHH).</li> <li><strong>Supplementary_file_2_GO_enrichments.xlsx: </strong>contains the complete results for the GO enrichment analysis for different gene datasets associated to: drought-CHH-DMRs, SINEs, MITEs, SINEs + MITEs.</li> <li><strong>italica_denovo_TE_280920.gff</strong>: contains the predicted TEs using the following methodology. First, TEs were de-novo annotated using the Extensive de-novo TE Annotator (EDTA) (version 1.8.3) (https://github.com/oushujun/EDTA) with default parameters, except for option --sensitive: 1, which uses RepeatModeler (version 2.0.1) to identify remaining TEs. All the steps in EDTA pipeline were selected (filter, final and anno) in order to perform whole-genome annotation/analysis after the TE library was constructed. Then, in the annotated library from EDTA, we merged overlapping fragments and fragments located at a close distance (<10bp) in a strand wise manner. The merged fragment was annotated as the family of longer merged fragment. Structural variants derived from nanopore data were used to redefine the boundaries of overlapping TE fragments to be more precise with actual predictions. LINE elements were identified independently by RepeatModeler in order to construct a more comprehensive de-novo TE library.</li> <li><strong>SaliS.fasta:</strong> contains the consensus sequences of <strong>Sali</strong>caceae <strong>S</strong>INE families (SaliS), the file was built by extracting information from the supplementary table 2 of the publication: "Divergence of 3′ ends as a driver of short interspersed nuclear element (SINE) evolution in the Salicaceae" (https://doi.org/10.1111/tpj.14721)</li> <li><strong>Pnigra_Italica_SaliS.bed: </strong>the file contains the annotated SaliS found by blastn over the P. nigra Italica reference genome (-qcov_hsp_perc 90 -perc_identity 70 -word_size 7). Column headers: chr, start, end, length, strand, perc_identity, SaliS family.</li> <li><strong>Pnigra_Italica_all_TEs_for_anno.bed: </strong>contains the merged information from <strong>italica_denovo_TE_280920.gff </strong>and<strong> Pnigra_Italica_SaliS.bed.</strong> Column headers: chr, start, end, length, strand, perc_identity (only for SaliS), TE superfamily.</li> <li><strong>CXX_ortet_DMRs_merged.bed</strong>: contains DMRs merged from all pairwise DMR callings between two ortets. One file per context. Column headers: chr, start, end, number of comparisons where the DMR occur, avg number of cytosines (when called in multiple DMR callings), avg differential methylation vs. control (when called in multiple DMR callings), avg adjusted p value (when called in multiple DMR callings), avg DMR length (when called in multiple DMR callings).</li> </ul> <p><strong>SCRIPTS</strong></p> <ul> <li><strong>cov_filtering.sh:</strong> to filter individual positions according to a custom threshold.</li> <li><strong>unionbedg_with_NAs.sh:</strong> to merge information from different samples in a single file taking into account the percentage of missing values per position across the given samples.</li> <li><strong>anovas_and_contrasts_boxplots_barplots_cld.r</strong>: to perform statistical tests for the effect of treatments and ortets on the average global methylation. Each sequence context was analyzed separately.</li> <li><strong>CHH_noise_filter.sh:</strong> to remove cytosines with invariable methylation values across 90% of the samples.</li> <li><strong>GlobalMethAvg_calculation.r</strong>: to calculate global average methylation given a methylation file (CpG.bed, CHG/bed or CHH.bed) and sample file.</li> <li><strong>Hclustering_and_PCAs_analysis.r:</strong> to perform hierarchical clustering, principal component analysis and plot the respective figures.</li> <li><strong>ICC_matrices_analysis.r:</strong> to calculate intraclass correlation coefficients among all pairwise combinations and plot colored grids</li> </ul> <p> </p> <p>Annotations are based on the de novo reference genome of the Populus nigra cv. Italica clone uploaded in the ENA project: PRJEB44889 (<a href="http://www.ebi.ac.uk/ena/browser/view/GCA_950102115">www.ebi.ac.uk/ena/browser/view/GCA_950102115</a>). Bisulfite sequencing data can be found under the ENA project: PRJEB51831</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
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.