miRcorrNet: Machine Learning-based Integration of miRNA and mRNA Expression Profiles, Combined with Feature Grouping and Ranking

This workflow allows you to make an integrated mRNA - miRNA profiles analysis.

miRcorrNet uses 2 different data sheets with same control-case column. It means you should have same samples in one column which should be both in mRNA and miRNA data sheet.

In mRNA data one should have samples in the rows and gene names in the columns but the type of the genes should be double. The "class" column represents the sample whether control or case. The type of class column should be String and there can be only 2 classes. Below one can see the some chunk of the mRNA data.

In miRNA data one should have samples in the rows and microRNA names in the columns but the type of the genes should be String. The "class" column represents the sample whether control or case. The type of class column should be String and there can be only 2 classes. Below one can see the some chunk of the miRNA data.

Find the full data set and documentation below in the "External resources" section.

External resources

• miRcorrNet (blog) - Malik Yousef Blog
• miRcorrNet (paper) - PubMed.gov
• miRcorrNet - GitHub repository by 'malikyousef'