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Dataset results
1,940 results for “data sample”
Bisulfite sequencing data of one human DNA sample
GEO Series GSE27239. Homo sapiens. 32 samples. Type: Methylation profiling by high throughput sequencing.
Affymetrix SNP array data for Monoclonal Gammopathies samples
GEO Series GSE31339. Homo sapiens. 84 samples. Type: Genome variation profiling by SNP array.
MicroRNA expression data obtained from skin samples of female pattern hair loss patients, healthy females and males
GEO Series GSE106780. synthetic construct; Homo sapiens. 13 samples. Type: Non-coding RNA profiling by array.
Gene expression data from glioblastoma tumor samples
Glioblastoma (GBM) is an incurable brain tumor carrying a dismal prognosis, which displays considerable heterogeneity. We have recently identified recurrent H3F3A mutations affecting two critical positions of histone H3.3 (K27, G34) in one-third of pediatric GBM. Here we show that each of these H3F3A mutations defines an epigenetic subgroup of GBM with a distinct global methylation pattern, and are mutually exclusive with IDH1 mutation (characterizing a CpG-Island Methylator Phenotype (CIMP) subgroup). Three further epigenetic subgroups were enriched for hallmark genetic events of adult GBM (EGFR amplification, CDKN2A/B deletion) and/or known transcriptomic signatures. We also demonstrate that the two H3F3A mutations give rise to GBMs in separate anatomic compartments, with differential regulation of OLIG1/2 and FOXG1, possibly reflecting different cellular origins. To further dissect the biological differences between epigenetic glioblastoma subgroups, we looked at the transcriptomic profiles of glioblastoma samples.
Sample data of human balance
<p>The data set comprises signals from the force platform (raw data for the force, moments of forces, and centers of pressure).</p>
Sample size data
<p>Abstracts of reports describing clinical trials matched with study sample sizes extracted from ct.gov. To be used to train our sample size tagger: https://github.com/ijmarshall/robotlabs/blob/master/sample_size/train-sample-size-model.ipynb. </p> <p> </p> <p> </p>
Culture KS Riboflavin spike experiment Version 2.0 10 mL samples Metabolomics Data
Open the record for dataset details and reuse information.
Sample Data
Open the record for dataset details and reuse information.
Random sample of forest stand data
<p>Random sample of open forest stand data</p>
EBD raw and processed Drugs data, generated samples.
Open the record for dataset details and reuse information.
Table A1: RNA-seq Data for shRNA PRLR vs shRNA NTC for 3 samples each in PEO-1.
<p><strong>Table A1: RNA-seq Data for shRNA PRLR vs shRNA NTC for 3 samples each in PEO-1.</strong></p> <p>Excel Workbooks for RNA seq analysis showing the differential expression results for shRNA PRLR vs shRNA NTC for 3 samples each in PEO-1.</p> <p>Samples F01_4 to F01_6 represent shRNA NTC PEO-1 and F01_7 to F01_9 represent shRNA PRLR PEO-1.</p> <p>Sheet 1: statistically significant up-regulated genes with log2fold change of >= 1 (sorted by fold change).</p> <p>Sheet 2: statistically significant down-regulated genes with log2fold change of <= -1 (sorted by fold change)</p> <p>Sheet 3: Statistically significant differentially expressed (DE) genes (p value =< 0.05 and p adj =< 0.05) including normalised counts for each sample (rounded values)</p> <p>Sheet 4: Differential expression analysis results (raw) including normalised counts for each sample.</p> <p>Sheet 5: Raw counts for the six samples (three replicates PEO-1 shRNA NTC and three replicates PEO-1 shRNA PRLR</p> <p>Sheet 6: Filtered normalised counts (all genes with row Sum less than one were removed)</p> <p>The data presented log2 fold change, lfcSE = standard error of the log2 Fold Change estimate, stat = Wald statistic and fold change are included</p>
Table A2: RNA-seq Data for shRNA PRLR vs shRNA NTC for 2 samples each in PEO-1.
<p><strong>Table A2: RNA-seq Data for shRNA PRLR vs shRNA NTC for 2 samples each in PEO-1.</strong></p> <p>A) Excel Workbooks for RNA seq analysis showing the differential expression results for shRNA PRLR vs shRNA NTC for 2 samples each in PEO-1.</p> <p>Samples F01_5 and F01_6 represent shRNA NTC PEO-1 and F01_7 to F01_8 represent shRNA PRLR PEO-1.</p> <p> </p> <p>Sheet 1: statistically significant up-regulated genes with log2fold change of >= 1 (sorted by fold change).</p> <p>Sheet 2: statistically significant down-regulated genes with log2fold change of <= -1 (sorted by fold change)</p> <p>Sheet 3: Statistically significant differentially expressed (DE) genes (p value =< 0.05 and p adj =< 0.05) including normalised counts for each sample (rounded values)</p> <p>Sheet 4: Differential expression analysis results (raw) including normalised counts for each sample.</p> <p>Sheet 5: Raw counts for the six samples (three replicates PEO-1 shRNA NTC and three replicates PEO-1 shRNA PRLR</p> <p>Sheet 6: Filtered normalised counts (all genes with row Sum less than one were removed)</p> <p>The data presented log2 fold change, lfcSE = standard error of the log2 Fold Change estimate, stat = Wald statistic and fold change are included.</p> <p> </p> <p>B) List of genes in the top up-regulated and down-regulated hallmark pathways, which were affected by PRLR knockdown in PEO-1 cells.</p> <p>Sheet 1: list of all (raw) hallmark pathways affected by knocking down PRLR generated by set enrichment analysis (GSEA) in R using the Bioconductor package fgsea.</p> <p>Sheet 2: list of significantly affected pathways with (p value =< 0.05 and p adj =< 0.05)</p> <p>Sheet 3: list of gene in Myc targets V1 pathway</p> <p>Sheet 4: list of gene in Myc targets V2 pathway</p> <p>Sheet 5: list of gene in epithelial mesenchymal transition pathway</p> <p>Sheet 6: list of gene in glycolysis pathway</p> <p>Sheet 7: list of gene in oxidative phosphorylation pathway.</p> <p>The data presented NES= normalised enrichment score, NE= enrichment score, n More Extreme= number of times a random gene set had a more extreme enrichment score value, log2 fold change, lfcSE = standard error of the log2 Fold Change estimate, stat = Wald statistic , fold change, p value, and read count are included.</p>
miRNA expression data from a cohort of Chilean Ulcerative Colitis human intestinal samples
GEO Series GSE133059. synthetic construct; Homo sapiens. 16 samples. Type: Non-coding RNA profiling by array.
Expression data from human glioma samples
GEO Series GSE12657. Homo sapiens. 25 samples. Type: Expression profiling by array.
Genome-wide bisulfite sequencing (Xmal-RRBS) of 50 breast cancer samples for jointly using with NGS and chromosomal microarray data
GEO Series GSE190126. Homo sapiens. 50 samples. Type: Methylation profiling by high throughput sequencing.
Expression data from platelets from early NSCLC and HNSCC patients in tumour presence and tumor free samples
GEO Series GSE244645. Homo sapiens. 69 samples. Type: Expression profiling by array.
Gene expression data from nine pediatric glioblastoma tumor samples
GEO Series GSE134404. Homo sapiens. 9 samples. Type: Expression profiling by array.
Expression data from Ewing's sarcoma tumor samples
GEO Series GSE37371. Homo sapiens. 39 samples. Type: Expression profiling by array.
Gene expression data of mRNA from skeletal muscle sample of pig DL and Pi breed
GEO Series GSE38518. Sus scrofa. 24 samples. Type: Expression profiling by array.
Affymetrix SNP array data for xenografted transient abnormal myelopoiesis samples
GEO Series GSE44739. Homo sapiens. 42 samples. Type: Genome variation profiling by SNP array; SNP genotyping by SNP array.
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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.