In this paper, we are concerned with identifying a subclass of tree ad
joining grammars (TAGs) that is suitable for the application to modeli
ng and predicting RNA secondary structures. The goal of this paper is
twofold: For the purpose of applying to the RNA secondary structure pr
ediction problem, we first introduce a special subclass of TAGs and de
velop a fast parsing algorithm for the subclass, together with some of
its language theoretic characterizations. Then, based on the algorith
m, we develop a prediction system and demonstrate the effectiveness of
the system by presenting some experimental results obtained from biol
ogical data, where free energy evaluation selection for parse trees is
incorporated into the algorithm. (C) 1999-Elsevier Science B.V. All r
ights reserved.