Recent Deep Learning Methodology Development for RNA–RNA Interaction Prediction

Genetic regulation of organisms involves complicated RNA–RNA interactions (RRIs) among messenger RNA (mRNA), microRNA (miRNA), and long non-coding (lncRNA). Detecting RRIs is beneficial for discovering biological mechanisms as well designing new drugs. In recent years, with more experimentally verified being deposited into databases, statistical machine learning, especially deep-learning-based automatic algorithms, have been widely applied to RRI prediction remarkable success. This paper first gives a brief introduction the traditional learning methods on benchmark databases training models, then provides methodology overview deep models in (miRNA)–mRNA (lncRNA)–miRNA interactions.