Resumen

PEIGNIER, Sergio  y  CASTANETA M., Heriberto. BÚSQUEDA DE ESTRUCTURAS SECUNDARIAS ÓPTIMAS Y SUBÓPTIMAS DE UNA CADENA DE ARN UTILIZANDO INTELIGENCIA ARTIFICIAL. Rev. Bol. Quim [online]. 2012, vol.29, n.2, pp.147-157. ISSN 0250-5460.

Ribonucleic acid (RNA) cannot exist in the form of linear chain, this molecule folds down for achieving its structure more stable through the formation of hydrogen bridges. The description of these bridges is called, the RNA secondary structure. From this, it is possible to deduce its tertiary structure of RNA. In many cases, this tertiary structure gives to RNA its properties, then, is interesting and important to know the secondary structure of the RNA chains. Find these structures using experimental techniques (X-ray crystallography) is slow and long, therefore, it is interesting predict these structures through computational techniques of prediction such as Artificial Intelligence. In the present work has been used a Hopfield neural network to find different secondary structures stable and an unidirectional multilayer neural network trained with real biological examples, in order to choose the secondary structure more structure next to a 'biological' real structure, between suboptimal structures encountered by the Hopfield network. This work was carried out (training of the second network, verification of the ability of prediction and validation) thanks to several samples of micro-RNA of drosophilas. Through these neural networks has been predicting a RNA secondary structure close to the "real" to a micro-RNA Sosophora Drosophila willistoni.

Palabras clave : RNA; Secondary Structure; Neural Network; Artificial Intelligence.

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