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Global properties of the genotype-phenotype map induced by RNA secondary structures can be described by random graph theory. The success of this approach depends on details of the respective secondary structure. A small selection of these dependencies, such as stem length, free energy and well-definedness, are analyzed in this paper. In addition, we present an algorithm, which, given a network that complies to a random graph model, provides estimates whether the network is connected or not. The algorithm is linear in time and in the sequence length, local connectivity provided, which is a graph property of the random graph model.
Published Online: 2009-11-03
Published in Print: 2002-02
