Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

ABSTRACT: The diversification and adaptation of Canary Island Descurainia

PROVIDER: PRJNA1060497 | ENA |

REPOSITORIES: ENA

ACCESS DATA

Json Xml

Dataset's files

Source:

			Action	DRS
	SRR27406221_1.fastq.gz	Fastqsanger.gz
	SRR27406221_2.fastq.gz	Fastqsanger.gz
	SRR27406222_1.fastq.gz	Fastqsanger.gz
	SRR27406222_2.fastq.gz	Fastqsanger.gz
	SRR27406223_1.fastq.gz	Fastqsanger.gz

Items per page:

1 - 5 of 31

Similar Datasets

tits

Project description:Phylogenetic study of Canary Island blue tits

| PRJEB7660 | ENA

Project description:Diversification and ecological niche evolution of Helianthemum in the Canary Islands

| PRJNA627098 | ENA

Genome-scale DNA methylation profiling of lung adenocarcinoma: validation using Ontario Tumor Bank samples

Project description:The independent population of lung adenocarcinoma and adjacent non-tumor lung used for verification of the EDRN/Canary Foundation study

2012-03-21 | GSE32866 | GEO

ddDesSoph

Project description:Descurainia sophia

| PRJEB81628 | ENA

Project description:High Parasite Diversity Accelerates Host Adaptation And Diversification

| PRJNA448370 | ENA

Project description:High Parasite Diversity Accelerates Host Adaptation And Diversification

| PRJNA448325 | ENA

Descurainia sophia

Project description:Descurainia sophia overview

| PRJNA643329 | ENA

Ovarian epithelial carcinoma tumors and cell lines

Project description:This SuperSeries is composed of the following subset Series: GSE27223: Ovarian Tumor Tissue Expression Study GSE27225: Canary Ovarian Cell Line Gene Expression Refer to individual Series

2011-02-12 | E-GEOD-27257 | biostudies-arrayexpress

Copy number variations distinguish lung adenocarcinomas from squamous cell carcinomas

Project description:For a number of clinical and biological reasons, the accurate classification of non-small cell lung carcinoma (NSCLC) into adenocarcinoma (ADC) and squamous cell carcinoma (SCC) is essential. DNA-based tests, which are not currently used, are more robust when applied to formalin-fixed paraffin-embedded tissues. To develop a molecular-based classification of NSCLC based on genome wide copy number variations (CNVs), the corresponding TCGA, SPORE and CANARY patient datasets were used as training and independent validation data. The signature genes were selected by advanced supervised classification algorithms and restricted to known important oncogenes/tumor suppressors, resulting in a final 27-gene signature that was able to classify ADC from SCC with 0.85-0.87 accuracies of SPORE validation sets and 0.96-0.98 accuracy of CANARY validation sets. Even by using the top 7 genes in this signature, the accuracies of the validation sets were still as high as 0.80 and 0.97, respectively. These signature genes also classified adenocarcinoma and squamous cell carcinomas from the non-malignant lung samples with accuracies of 91-97%.

2015-11-13 | GSE74948 | GEO

Descurainia sophioides

Project description:Descurainia sophioides Genome sequencing

| PRJNA214274 | ENA