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289
datasets available to search
ShareScore release 0.9.0
Dataset results
289 results for “Genomic prediction”
Genome-wide Localization of SREBP-2 in Hepatic Chromatin Predicts a Novel Role in Autophagy
GEO Series GSE28084. Mus musculus. 8 samples. Type: Expression profiling by array; Genome binding/occupancy profiling by high throughput sequencing.
Viral Status Predicts Patterns of Genome Methylation and Decitabine Response in Merkel Cell Carcinoma [RNA-Seq]
GEO Series GSE176466. Homo sapiens. 50 samples. Type: Expression profiling by high throughput sequencing.
Comprehensive Analyses of 723 Transcriptomes Enhance GWAS Biological Interpretation and Genomic Prediction for Complex Traits in Cattle
GEO Series GSE128075. Bos taurus. 94 samples. Type: Expression profiling by high throughput sequencing.
Predicting genome-wide DNA methylation
GEO Series GSE62992. Homo sapiens. 100 samples. Type: Methylation profiling by genome tiling array.
Whole genome expression profiling based on paraffin embedded tissue can be used to classify diffuse large b-cell lymphoma and predict clinical outcome
GEO Series GSE32918. Homo sapiens. 249 samples. Type: Expression profiling by array.
Genomic aberrations predicts survival in clear cell renal cell carcinoma
GEO Series GSE30460. Homo sapiens. 125 samples. Type: SNP genotyping by SNP array.
Early-Stage Lung adenocarcinoma MDM2 genomic heterogeneity predicts clinical outcome and response to targeted therapy
GEO Series GSE191171. Homo sapiens. 12 samples. Type: Expression profiling by high throughput sequencing.
Identifying Multiple Genomic Abnormalities and Predicting Neoantigens from Single Tumor Cells [PRJNA1110293]
GEO Series GSE267871. Mus musculus. 27 samples. Type: Other.
Comparative chemical-genomic profiling of plant-based hydrolysate toxins enables predictive assessment of responses to complex mixtures
GEO Series GSE186866. Saccharomyces cerevisiae. 151 samples. Type: Other.
A functional genomics predictive network model identifies regulators of inflammatory bowel disease: Ribo-zero RNAseq mouse distal colon DSS Colitis model of genetically engineered mice
GEO Series GSE83550. Mus musculus. 194 samples. Type: Expression profiling by high throughput sequencing.
Genomic copy number variations in the genomes of leukocytes predict prostate cancer clinical outcomes
GEO Series GSE70650. Homo sapiens. 273 samples. Type: Genome variation profiling by SNP array.
Data from: Improving accuracies of genomic predictions for drought tolerance in maize by joint modeling of additive and dominance effects in multi-environment trials
Breeding for drought tolerance is a challenging task that requires costly, extensive and precise phenotyping. Genomic selection (GS) can be used to maximize selection efficiency and the genetic gains in maize (Zea mays L.) breeding programs for drought tolerance. Here we evaluated the accuracy of genomic selection of additive (A) against additive+dominance (AD) models to predict the performance of untested maize single-cross hybrids for drought tolerance in multi-environment trials. Phenotypic data of five drought-tolerance traits were measured in 308 hybrids in eight trials under water-stressed (WS) and well-watered (WW) conditions over two years and two locations in Brazil. Hybrids' genotypes were inferred based on their parents' genotypes (inbred lines) using single nucleotide polymorphism data obtained via genotyping-by-sequencing. GS analyses were performed using genomic best linear unbiased prediction by fitting a factor analytic (FA) multiplicative mixed model. Results showed differences in the predictive accuracy between A and AD models for the five traits under consideration in both water conditions. For grain yield (GY), the AD model doubled the predictive accuracy in comparison to the A model. FA framework allowed for investigating the stability of additive and dominance effects across environments, as well as the additive- and dominance-by-environment interactions, with interesting applications for parental and hybrid selection. Prediction performance of untested hybrids using GS that benefit from borrowing information from correlated trials increased 40% and 9% for A and AD models, respectively. These results highlighted the importance of multi-environment trial analysis with GS that incorporate dominance effects into genomic predictions of GY in maize single-cross hybrids.
Imaging and Genomic Biomarkers to Predict Response in Prostate Cancer
ClinicalTrials.gov study NCT05477823. IPD Sharing: NO. Countries: 1. Publications: 0.
Genomics in Infection and Sepsis to Predict Organ Dysfunction and Outcomes in Sepsis
ClinicalTrials.gov study NCT04199962. IPD Sharing: UNDECIDED. Countries: 1. Publications: 0.
Ribociclib&Belinostat In Patients w Metastatic Triple Neg Breast Cancer & Recurrent Ovarian Cancer w Response Prediction By Genomics
ClinicalTrials.gov study NCT04315233. IPD Sharing: NO. Countries: 1. Publications: 0.
East Asian Breast Cancer Genome Atlas and Recurrence Risk Prediction
ClinicalTrials.gov study NCT04344496. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Proteomics and Genomics Combined With CT to Predict CVD
ClinicalTrials.gov study NCT05800093. IPD Sharing: NO. Countries: 1. Publications: 0.
Genome-wide Pharmacogenetic Candidate Gene Single Nucleotide Polymorphism (SNP) Array-based Approach to Predict Chemoresponse and Survival in Patients With Acute Myeloid Leukemia With Normal Karyotype
ClinicalTrials.gov study NCT01066338. IPD Sharing: Not stated. Countries: 1. Publications: 0.
Validation of Genomic Immune-phenotyping Profiles to Predict Risk of Kidney Transplant Rejection
ClinicalTrials.gov study NCT04727788. IPD Sharing: NO. Countries: 4. Publications: 0.
Study of Pembrolizumab in Metastatic Biliary Tract Cancer as Second-line Treatment After Failing to at Least One Cytotoxic Chemotherapy Regimen: Integration of Genomic Analysis to Identify Predictive
ClinicalTrials.gov study NCT03110328. IPD Sharing: Not stated. Countries: 1. Publications: 0.
ScienceDex guides
Understand access before you commit
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.