A neural network hamiltonian governing the formation of RNA base‐pairing patterns
Ariel Fernández, Alejandro Belinky · Berichte der Bunsengesellschaft für physikalische Chemie · 1994
Abstract We implement a neural network associating a two‐state unit to each pair of bases in a fixed RNA sequence. The connectivity matrix is constructed following the cooperativity rules of nucleation for RNA hairpin formation and base‐pair stacking. Attractive neural patterns correspond to stable RNA secondary structures. Moreover, the Gibbs probability of a pattern coincides with the Boltzmann weight of the corresponding structure.