The RNA secondary structure prediction problem (2˚RNA) is a critical one in molecular biology. Secondary structure can be determined directly by x-ray diffraction, but this is difficult, slow, and expensive. Moreover, it is currently impossible to crystallize most RNAs. Mathematical models for prediction

Folding of RNA sequences into biologically functional secondary structures has been studied by different theoretical approaches since the early seventies. The most popular algorithm is based on thermodynamic assumptions of the folding procedure [9, 5, 2]. In addition algorithms based on the kinetics of folding were developed [4, 6]. All these algorithms predict a defined secondary structure or a set of possible suboptimal structures for every single sequence. With increasing chain length of the molecules the differences between the obtained prediction and the phylogenetically derived or experimental proofed structures increases dramatically [1, 3]. Our current investigations are divided into the improvement and extension of the prediction algorithms implemented in the Vienna RNA package [2]. In addition experimental studies of the secondary structure of RNA viruses are performed in order to provide structural information that can be used as constraints in the folding algorithm. The aim...

RNA molecules are involved in numerous key cellular processes. Recent findings consolidated the current view that RNA is no longer regarded solely as a passive transporter of the genetic code, but as an extremely versatile class of molecules actively participating in all steps of gene expression. Major objectives are the design and preparation of RNA molecules with predicted structure and function in order to tackle hitherto unsolvable medical and pharmaceutical problems. Transfer RNAs provide excellent models for the determination of new properties, which mostly can be interpreted as features of RNA molecules in general.

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Abstract — Recently it is recognized as a very important research topic to simulate kinetic folding of an RNA molecule in order to understand its functionality in vivo. In this paper, we will propose a new approach to simulating kinetic folding of an RNA molecule based on a new idea of “enumerating secondary structures by a graph. ” Although most of the previous works try to reduce the conformation space of a given RNA molecule in order to escape from the combinatorial explosion problem, the present paper gives us an efficient and approximate simulation methodology for hairpin formation with keeping the conformation space completely. As far as the authors ’ knowledge, this is the first polynomial update time simulation algorithm for kinetic folding analysis of an RNA molecule which has a nice theoretical property that the convergence point of its simulation always exactly coincides with the equilibrium distribution of secondary structures of the RNA molecule. We evaluated the time efficiency and the accuracy of the proposed method against the exhaustive method which numerically simulates the master equation by completely generating all secondary structures. The results show that the proposed method is much faster than the exhaustive method and that the proposed method gives us well approximated simulation results.