The key to understanding the role of microRNA in human disease is in the proficient identification of target genes regulated by microRNA. However, deciphering the relevance of the large number of mRNAs predicted or demonstrated to be targeted by microRNAs can be an overwhelming bioinformatics challenge.
IPA’s microRNA Target Filter and analytics enable bench scientists to use biological annotation in combination with experimental data to identify high priority mRNA targets, and rapidly refine an initial large list of targets to a set of biologically compelling, high quality microRNA and mRNA worthy of further investigation.
IPA incorporates experimentally demonstrated and predicted microRNA-mRNA interactions from the databases TarBase, miRecords, and TargetScan, as well as from peer-reviewed microRNA original research articles as the content base for the microRNA Target Filter.
IPA’s ability to prioritize microRNA and mRNA hits based on biological context is key to overcoming the inherent complexity in microRNA data analysis. Whether you are starting with microRNA or mRNA data, focus your analysis using the following criteria from the Ingenuity Knowledge Base:
- Level of quality of a predicted microRNA-mRNA target relationship
- Agreement between predicted effect of a microRNA-mRNA interaction and your experimental data; for example, cases where upregulation of a microRNA and downregulation of its mRNA target have been observed.
- microRNA and mRNA that have a functional associations with a disease, cellular process, or pathway relevant to your experimental model