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87
datasets available to search
ShareScore release 0.9.0
Dataset results
87 results for “candidate gene identification”
Identification of novel type 2 diabetes candidate genes involved in the crosstalk between the mitochondrial and the insulin signaling systems: chronic insulin treatment
GEO Series GSE39317. Mus musculus. 6 samples. Type: Expression profiling by array.
Identification of novel type 2 diabetes candidate genes involved in the crosstalk between the mitochondrial and the insulin signaling systems
GEO Series GSE39320. Mus musculus. 20 samples. Type: Expression profiling by array.
Identification of candidate Arabidillo target genes in Arabidopsis
GEO Series GSE6826. Arabidopsis thaliana. 12 samples. Type: Expression profiling by array.
Identification of candidate genes associated with the double flower of Brassica napus using RNA-seq
GEO Series GSE271208. Brassica napus. 6 samples. Type: Expression profiling by high throughput sequencing.
Identification of candidate genes related to astringency in cucumber via RNA-seq based transcriptome profiling
GEO Series GSE112666. Cucumis sativus. 6 samples. Type: Expression profiling by high throughput sequencing.
Identification of novel type 2 diabetes candidate genes involved in the crosstalk between the mitochondrial and the insulin signaling systems: TP53inp2 (DOR) RNAi knock-downs
GEO Series GSE39318. Mus musculus. 8 samples. Type: Expression profiling by array.
Identification of genomic regions and candidate genes associated with body weight and body conformation traits in Karachai goats
<p>The objective of this study was to investigate the genomic regions and candidate genes related to body weight and body conformation traits in Karachai goats at age 8 months in Russia by using genome wide association study (GWAS), we genotyped 269 goats and 53347 informative SNPs. SNPs were identified for all traits studied at age 8 months: body weight (5 SNPs), withers height (7 SNPs), rump height (9 SNPs), body length (6 SNPs), chest perimeter (4 SNPs), chest witdth (30 SNPs), chest depth (1 SNPs) and Rump width (5 SNPs). The most significant number of candidate genes was identified at Chr13 (33 candidate genes for the 5 traits). The most significant genes for body weight are <em>CRADD, HMGA2, MSRB3, MAX, HACL1 and RAB15</em>, which are growth factors with high expression in cell growth and development in animal body. <em>APOB, PTPRK, BCAR1</em>, <em>AOAH and ASAH1</em> genes have been associated with withers height, rump height and body length, these genes regulate metabolism process in cells and are involved in various metabolic processes, including fatty acid metabolism and lipopolysaccharide catabolism. Also, <em>WDR70, ZBTB24 </em>and <em>SORCS3</em> genes were linked to chest width. <em>KCNG4</em> was associated with rump height, body length and chest perimeter. The identificated candidate genes can be used as a molecular marker for growth traits selection in goats, which increase genetic improvement in russian goat breeds.</p>
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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.