microRNAs (miRNAs) are short non-coding regulatory RNA molecules. The activity of a miRNA in a biological process can often be reflected in the expression program that characterizes the outcome of the activity. We introduce a computational approach that infers such activity from high-throughput data using a novel statistical methodology, called minimum-mHG (mmHG), that examines mutual enrichment in two ranked lists.
MicroRNAs (miRNAs) are critical regulators in the complex cellular networks. The mirAct web server (http://sysbio.ustc.edu.cn/software/mirAct) is a tool designed to investigate miRNA activity based on gene-expression data by using the negative regulation relationship between miRNAs and their target genes. mirAct supports multiple-class data and enables clustering analysis based on computationally determined miRNA activity.
MicroRNAs (miRNAs) play a key role in regulating tumor progression and metastasis. Identifying key miRNAs, defined by their functional activities, can provide a deeper understanding of biology of miRNAs in cancer. However, miRNA expression level cannot accurately reflect miRNA activity.
RNAi screens are widely used in functional genomics. Although the screen data can be susceptible to a number of experimental biases, many of these can be corrected by computational analysis. For this purpose, here we have developed a web-based platform for integrated analysis and visualization of RNAi screen data named CARD (for Comprehensive Analysis of RNAi Data; available at https://card.niaid.nih.gov).
Our database aim to make it easy for researchers to find the right tools or data source for their own specific study in miRNA field. Now we have collect >1000 tools. This database will update when every new 100 tools add in. Last update time 22nd April, 2018 (v1.2).
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