miRDiabetes : A microRNA-Diabetes Association Database Constructed With Data Mining on Literature

Abstract

MicroRNAs (miRNAs) are a growing class of non-coding RNAs that regulate gene expression by translational repression. A role for miRNA in diabetes was first established in 2004 and research in miRNA-diabetes association has been an increasing interest since then. However, no effort or computational tool has been put forward to retrieve and gather literature on this topic. In this research, we have designed and implemented a method of utilizing data mining techniques on textual data on this subject, which can automatically determine relevancy of new entries with high accuracy. With this method, we have constructed miRDiabetes, the first comprehensive database to collect information in publications from PubMed that profiles relations between miRNAs and diabetes. We have also developed an application to facilitate future updates and built a website for researchers to search and download the miRDiabetes database.