Michael Fernández

According to our database, Michael Fernández authored at least 14 papers between 2005 and 2022.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2022

The transformational role of GPU computing and deep learning in drug discovery.

Mohit Pandey, Michael Fernández, Francesco Gentile, Olexandr Isayev, Alexander Tropsha, Abraham C. Stern, Artem Cherkasov

Nat. Mach. Intell., 2022

2020

DeepCOP: deep learning-based approach to predict gene regulating effects of small molecules.

Godwin Woo, Michael Fernández, Michael Hsing, Nathan A. Lack, Ayse Derya Cavga, Artem Cherkasov

Bioinform., 2020

2019

Quantitative Structure-Price Relationship (QS$R) Modeling and the Development of Economically Feasible Drug Discovery Projects.

Michael Fernández, Fuqiang Ban, Godwin Woo, Olexandr Isayev, Carl Perez, Valery Fokin, Alexander Tropsha, Artem Cherkasov

J. Chem. Inf. Model., 2019

2018

Toxic Colors: The Use of Deep Learning for Predicting Toxicity of Compounds Merely from Their Graphic Images.

Michael Fernández, Fuqiang Ban, Godwin Woo, Michael Hsing, Takeshi Yamazaki, Eric Leblanc, Paul S. Rennie, William J. Welch, Artem Cherkasov

J. Chem. Inf. Model., 2018

2017

Machine Learning for Silver Nanoparticle Electron Transfer Property Prediction.

Baichuan Sun, Michael Fernández, Amanda S. Barnard

J. Chem. Inf. Model., October, 2017

2015

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

Michael Fernández, Hongqing Shi, Amanda S. Barnard

J. Chem. Inf. Model., 2015

2014

Near-Rand: Noise-based location obfuscation based on random neighboring points.

Mayra Zurbarán, Karen Ávila, Pedro M. Wightman, Michael Fernández

Proceedings of the IEEE Latin-America Conference on Communications, 2014

2011

Prediction of dinucleotide-specific RNA-binding sites in proteins.

Michael Fernández, Yutaro Kumagai, Daron M. Standley, Akinori Sarai, Kenji Mizuguchi, Shandar Ahmad

BMC Bioinform., 2011

2010

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

Michael Fernández, Shandar Ahmad, Akinori Sarai

J. Chem. Inf. Model., 2010

2009

Recognition of Drug-Target Interaction Patterns using Genetic Algorithm-optimized Bayesian-regularized Neural Networks and Support Vector Machines.

Michael Fernández, Akinori Sarai, Shandar Ahmad

Proceedings of the IEEE International Conference on Systems, 2009

2008

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

Syed Zahid Ahmed, Julien Eydoux, Michael Fernández, Laurent Rouge, Gilles Sassatelli, Lionel Torres

Proceedings of the ReConFig'08: 2008 International Conference on Reconfigurable Computing and FPGAs, 2008

2006

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

Julio Caballero, Leyden Fernández, José Ignacio Abreu, Michael Fernández

J. Chem. Inf. Model., 2006

2005

Modeling of Cyclin-Dependent Kinase Inhibition by 1<i>H</i>-Pyrazolo[3, 4-<i>d</i>]Pyrimidine Derivatives Using Artificial Neural Network Ensembles.

Michael Fernández, Alain Tundidor-Camba, Julio Caballero

J. Chem. Inf. Model., 2005

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, Miguel Garriga, Michael Fernández

J. Comput. Aided Mol. Des., 2005