Experiment ID | EXP00033 |
Reference | Title: Using expression profiling data to identify human microRNA targets. Author: Huang JC, Babak T, Corson TW, Chua G, Khan S, Gallie BL, Hughes TR, BlencoweBJ, Frey BJ, Morris QD. Journal: Nat Methods. 2007 Dec;4(12):1045-9. Epub 2007 Nov 18. Abstract: We demonstrate that paired expression profiles of microRNAs (miRNAs) and mRNAscan be used to identify functional miRNA-target relationships with highprecision. We used a Bayesian data analysis algorithm, GenMiR++, to identify anetwork of 1,597 high-confidence target predictions for 104 human miRNAs, whichwas supported by RNA expression data across 88 tissues and cell types, sequencecomplementarity and comparative genomics data. We experimentally verified ourpredictions by investigating the result of let-7b downregulation inretinoblastoma using quantitative reverse transcriptase (RT)-PCR and microarrayprofiling: some of our verified let-7b targets include CDC25A and BCL7A. Comparedto sequence-based predictions, our high-scoring GenMiR++ predictions had muchmore consistent Gene Ontology annotations and were more accurate predictors ofwhich mRNA levels respond to changes in let-7b levels. PMID: 18026111 |
Expressiion Profile | Description: Profiling miRNAs in human retinoblastoma Organism: Homo sapiens GEO ID: GSE7072 Platform: GPL4879 Number of samples: 6 |
Design and Sample | Cancer Type: retinoblastoma Cancer SubType: N/D Cell Line: N/D Experimental Design: cancer vs normal Case Sample: retinoblastoma Control Sample: normal retina Num of Case: 3 Num of Control: 3 Quantification Software: Limma Num of miRNAs: 163 |
Identification | Num of Up: 0 Num of Down: 3 |