ALGORITHM INDEPENDENT PROPERTIES OF RNA SECONDARY STRUCTURE PREDICTIONS

Algorithms predicting RNA secondary structures based on different fold ing criteria - minimum free energies (mfe), kinetic folding (kin), max imum matching (mm)- and different parameter sets are studied systemati cally. Two base pairing alphabets were used: the binary GC and the nat ural four-letter AUGC alphabet. Computed structures and free energies depend strongly on both the algorithm and the parameter set. Statistic al properties, such as mean number of base pairs, mean numbers of stac ks, mean loop sizes, etc., are much less sensitive to the choice of pa rameter set and even of algorithm. Some features of RNA secondary stru ctures, such as structure correlation functions, shape space covering and neutral networks, seem to depend only on the base pairing logic (G C or AUGC alphabet).