Michael Fernández

Proteochemometric Recognition of Stable Kinase Inhibition Complexes Using Topological Autocorrelation and Support Vector Machines

Shandar Ahmad, Akinori Sarai, Michael Fernández, 2010, J. Chem. Inf. Model..

Genetic neural network modeling of the selective inhibition of the intermediate-conductance Ca2+-activated K+ channel by some triarylmethanes using topological charge indexes descriptors

Julio Caballero, Michael Fernández, Miguel Garriga, 2005, J. Comput. Aided Mol. Des..

Amino Acid Sequence Autocorrelation Vectors and Ensembles of Bayesian-Regularized Genetic Neural Networks for Prediction of Conformational Stability of Human Lysozyme Mutants

José Ignacio Abreu Salas, Julio Caballero, Michael Fernández, 2006, J. Chem. Inf. Model..

Large-scale recognition of high-affinity protease–inhibitor complexes using topological autocorrelation and support vector machines

Shandar Ahmad, Akinori Sarai, Michael Fernández, 2016 .

Power Consumption Reduction Explorations in Processors by Enhancing Performance Using Small ESL Reprogrammable eFPGAs

Lionel Torres, Gilles Sassatelli, Syed Zahid Ahmed, 2008, 2008 International Conference on Reconfigurable Computing and FPGAs.

Quantitative Structure-Property Relationship Modeling of Electronic Properties of Graphene Using Atomic Radial Distribution Function Scores

Michael Fernández, Amanda S. Barnard, Hongqing Shi, 2015, J. Chem. Inf. Model..

Recognition of drug-target interaction patterns using genetic algorithm-optimized Bayesian-regularized neural networks and support vector machines

Shandar Ahmad, Akinori Sarai, Michael Fernández, 2009, 2009 IEEE International Conference on Systems, Man and Cybernetics.

Prediction of dinucleotide-specific RNA-binding sites in proteins

Shandar Ahmad, Kenji Mizuguchi, Akinori Sarai, 2011, BMC Bioinformatics.