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]
@article{FloridoPRGGU13,
title = {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},
author = {Javier P. Florido and Héctor Pomares and Ignacio Rojas and Alberto Guillén and Francisco M. Ortuño Guzman and José M. Urquiza},
year = {2013},
doi = {10.1016/j.neucom.2012.11.040},
url = {http://dx.doi.org/10.1016/j.neucom.2012.11.040},
researchr = {https://researchr.org/publication/FloridoPRGGU13},
cites = {0},
citedby = {0},
journal = {Neurocomputing},
volume = {121},
pages = {64-78},
}