Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

MiRNA expression-based, individualized outcome prediction for SDT treatment in melanoma

ABSTRACT: Individualized outcome prediction classifiers were successfully constructed through expression profiling of a total of 3100 capture probes, covering all human, mouse and rat microRNAs annotated in miRBase 18.0, in 8 melanoma samples divided into 4 groups (Control, ALA, US, and SDT group).

ORGANISM(S): synthetic construct Mus musculus

PROVIDER: GSE65390 | GEO | 2015/01/29

SECONDARY ACCESSION(S): PRJNA273868

REPOSITORIES: GEO

ACCESS DATA

Json Xml

Similar Datasets

miRNA expression-based, individualized outcome prediction for SDT treatment in melanoma

Project description:Individualized outcome prediction classifiers were successfully constructed through expression profiling of a total of 3100 capture probes, covering all human, mouse and rat microRNAs annotated in miRBase 18.0, in 8 melanoma samples divided into 4 groups (Control, ALA, US, and SDT group). In the study presented here, a consecutively operated, well-defined cohort of 8 melanoma cases was used to acquire miRNA expression profiles with Exiqon arrays based on miRBase 18.0.

2015-01-29 | E-GEOD-65390 | biostudies-arrayexpress

ncRNA expression-based, individualized outcome prediction for CRC patients

Project description:Individualized outcome prediction classifiers were successfully constructed through expression profiling of ncRNAs in 165 CRC cases.

2016-12-28 | GSE92928 | GEO

Gene expression-based, individualized outcome prediction for autism

2015-04-17 | GSE67979 | GEO

Gene expression-based, individualized cancer progression outcome prediction for S61 stable transfectants

Project description:Individualized outcome prediction classifiers were successfully constructed through expression profiling in stable transfectants

2016-04-26 | GSE80641 | GEO

Gene silenced-based, individualized cancer progression outcome prediction for shATMIN stable transfectants

Project description:Individualized outcome prediction classifiers were successfully constructed through expression profiling in stable transfectants

2019-05-25 | GSE81866 | GEO

Gene expression-based, individualized outcome prediction for RUNX1T1 Knock-down treated ECFCs

Project description:Individualized outcome prediction classifiers were successfully constructed through expression profiling of RUNX1T1 mediated.

2017-08-17 | GSE86594 | GEO

MiRNA-expression based, individualized outcome prediction for the cardiovascular disease patients

2014-05-04 | GSE53675 | GEO

Gene expression-based, individualized outcome prediction for autism

Project description:Individualized outcome prediction classifiers were successfully constructed through expression profiling of 91 up-regulated and 67 down-regulated miRNAs in 5 autism spectrum disorder (ASD) cases and 5 controls. In the study presented here, a well-defined cohort of 5 autism spectrum disorder cases and 5 controls was used to acquire expression profiles of 91 up-regulated and 67 down-regulated miRNAs, leading to the first global miRNA expression profile of ASD in China.

2015-04-17 | E-GEOD-67979 | biostudies-arrayexpress

MiRNA-expression based, individualized outcome prediction for the cardiovascular disease patients

Project description:Individualized outcome prediction classifiers were successfully constructed through expression profiling of a total of 2,500 miRNAs in 13 cardiovascular disease patients and 5 healthy controls In the study presented here, a well-defined cohort of 13 cardiovascular disease cases and 5 healthy controls was used to acquire expression profiles of a total of 2,500 unique genes.

2014-05-04 | E-GEOD-53675 | biostudies-arrayexpress

Gene expression-based, individualized outcome prediction for surgically treated lung cancer patients

Project description:Individualized outcome prediction classifiers were successfully constructed through expression profiling of a total of 8,644 genes in 50 non-small cell lung cancer (NSCLC) cases, which had been consecutively operated on within a defined short period of time and followed up more than five years. The resultant classifier of NSCLCs yielded 82% accuracy for forecasting survival or death five years after surgery of a given patient. In addition, since two major histologic classes may differ in terms of outcome-related expression signatures, histologic type-specific outcome classifiers were also constructed. The resultant highly predictive classifiers, designed specifically for non-squamous cell carcinomas, showed a prediction accuracy of more than 90% independent of disease stage. In addition to the presence of heterogeneities in adenocarcinomas, our unsupervised hierarchical clustering analysis revealed for the first time the existence of clinicopathologically relevant subclasses of squamous cell carcinomas with marked differences in their invasive growth and prognosis. This finding clearly suggests that NSCLCs comprise distinct subclasses with considerable heterogeneities even within one histologic type. Overall, these findings should advance not only our understanding of the biology of lung cancer but also our ability to individualize post-operative therapies based on the predicted outcome. Keywords: cell type comparison and prognosis prediction

2007-01-20 | GSE4716 | GEO

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data