Role of Bioinformatics in Non-coding RNA Analysis

The transcriptome, comprising RNA molecules expressed in cells or tissues, is predominantly composed of non-coding RNAs (ncRNAs), which has most of the region in the genome of humans. The classification of ncRNAs includes housekeeping and regulatory ncRNAs, with the latter encompassing long-ncRNAs (lncRNAs), microRNAs (miRNAs), and small interfering RNAs (siRNAs). These ncRNAs, including lncRNAs, play a crucial role in various levels of gene regulation, like transcription, RNA processing, translation, and chromatin modification. By interacting with RNA, DNA, and proteins, lncRNAs influence chromatin structure and the localization and activity of various protein complexes and RNA processing. The study of lncRNAs presents both challenges and opportunities, as they exhibit complex sequence and structural characteristics. The application of bioinformatics in the study of ncRNAs highlights how computational methods have contributed to the prediction and identification of novel ncRNAs, target gene prediction, RNA structure prediction, evolutionary analysis, functional prediction, and the construction of regulatory networks. This chapter briefly discusses the databases and tools that aid in the analysis and interpretation of ncRNA data, including LncTarD, LnCeVar, MirGeneDB, miRTarBase, SEAweb, DIANA-LncBase, miRPathDB, RNAInter, oRNAment, miRDB, ENCORI, NPInter, etc. These resources provide valuable information on ncRNA interactions, targets, functions, and regulation, enabling researchers to explore the complex world of ncRNAs.