Print |

You have not viewed any products recently.

 

microRNA & piRNA Research

Cooperative miRNA Target Prediction and GO & Pathway Analysis

 

Cooperative miRNA Target Prediction

In an attempt to highlight potentially significant targets of differentially expressed miRNAs, we identify cooperative miRNA targets for multiple enriched miRNAs using Arraystar's proprietary miRNA target database (Figure 1). Since a lot of genes are predicted to be targets of numerous miRNAs, miRNA targets are weighted based on their total number of predicted target sites for co-expressed miRNAs. To compensate for potential bias, the rank score of a miRNA target is calculated by dividing the number of target sites for co-expressed miRNAs by the total number of target sites for the gene. We use a cutoff value (>0.15) to derive a relatively small group of miRNA target genes that are strong candidates for cooperative targeting by enriched miRNAs.

201012215031423

Figure 1. To obtain most reliable miRNA target information, we set up our own proprietary miRNA target database. A predicted miRNA target collected to Arraystar miRNA target database must be supported by at least three public miRNA target databases such as miRBase, miRanda, TargetScan.

GO Analysis

We identify significantly enriched "biological process" GO terms in the list of predicted targets of enriched miRNAs (p<0.01).

20101222036993

Figure 2. Clustering of over-represented Gene Ontology (GO) classes in predicted targets of differential microRNAs. Shown are heat map representations of GO terms over-represented among predicted cooperative targets (Y-axis) of enriched miRNAs. All genes with statistically over-represented GO annotation are included (p<0.01, x-axis) as identified by GoStat.

Learn more about Arraystar microRNA sequencing service>

Reference

1. Ryan D. Morin, Michael D. O' Connor, Malachi Griffith, et al. Application of massively parallel sequencing to microRNA profiling and discovery in human embryonic stem cells. Genome Res. 2008 18: 610-621

 

 

Back to news

Publications >>

mRNA&LncRNA Epitranscriptomic Array
METTL3/IGF2BP3 axis inhibits tumor immune surveillance by upregulating N6-methyladenosine modification of PD-L1 mRNA in breast cancer. Wan W, et al. Molecular Cancer, 2022​

Full text>>

circRNA Epitranscriptomic Array
METTL14-mediated m6A modification of circORC5 suppresses gastric cancer progression by regulating miR-30c-2-3p/AKT1S1 axis. Fan H N, et al. Molecular Cancer, 2022​

Full text>>

 

Promotion >>

10% OFF CircRNA Profiling 
Valid 11/01/2022 - 1/31/2023

Accurate CircRNA Profiling with Rich Analysis
Cited by +500 publications 


Request Quote>>

 

Brochures >> 

Arraystar Small RNA Array
miRNA, pre-miRNA, tRNA, tsRNA, snoRNA

The new way of sensitive, accurate, simultaneous profiling of major small RNA classes

Small_RNA_Brochure

Download.pdf

 

Webinars >>

​​The Latest Highlights on CircRNA in Cancer

youtube_circ_cover

Watch video


New Discoveries in m6A Epitranscriptomics

youtube_m6A_cover

Watch video


How to Study LncRNA Expression and Modifications?

Lnc_exp_and_mod

Watch video


Raising the Bar of Multi-transcrptomic Profiling of Small RNAs

Small_RNA_Array_Webinar

Watch video