An effective, practical and low computational cost framework for the integration of heterogeneous data to predict functional associations between proteins by means of Artificial Neural Networks

Javier P. Florido, Héctor Pomares, Ignacio Rojas, Alberto Guillén, Francisco M. Ortuño Guzman, José M. Urquiza. An effective, practical and low computational cost framework for the integration of heterogeneous data to predict functional associations between proteins by means of Artificial Neural Networks. Neurocomputing, 121:64-78, 2013. [doi]

Authors

Javier P. Florido

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Héctor Pomares

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Ignacio Rojas

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Alberto Guillén

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Francisco M. Ortuño Guzman

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José M. Urquiza

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