A new method for predicting RNA secondary structure

Abstract

It has become clear recently that there are many RNAs that are not translated into proteins, instead they work as functional molecules. These RNAs are called "noncoding RNAs." Predicting the secondary structure of these RNAs is important for understanding their functions. We focus on Nussinov's algorithm and the SCFG version of Nussinov's algorithm as useful techniques for predicting RNA secondary structures. We introduce a new scoring table and loop length restriction to improve these algorithms, and the improved algorithms provided better levels of performance than the originals.