ToppMiR: ranking microRNAs in biological context

Identifying functionally significant microRNAs and their correspondingly most important messenger RNA targets in specific biological contexts is a critical task to improve our understanding of molecular mechanisms underlying organismal development, physiology and disease. We have developed ToppMiR, a web-based analytical workbench that allows miRs and mRNAs to be co-analyzed via biologically centered approaches in which gene function associated annotations are used to train a machine learning-based analysis engine.

ToppMiR learns about biological contexts based on gene associated information from expression data or from a user-specified set of genes that relate to context-relevant knowledge or hypotheses. Within the biological framework established by the genes in the training set, its associated information content is then used to calculate a features association matrix composed of biological functions, protein interactions and other features. This scoring matrix is then used to jointly rank both the test/candidate miRs and mRNAs. ToppMir is publicly available.