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2020 – today
- 2022
[j11]Mohit Pandey
, Michael Fernández, Francesco Gentile, Olexandr Isayev, Alexander Tropsha, Abraham C. Stern, Artem Cherkasov:
The transformational role of GPU computing and deep learning in drug discovery. Nat. Mach. Intell. 4(3): 211-221 (2022)- 2020
- [j10]Godwin Woo, Michael Fernández, Michael Hsing, Nathan A. Lack, Ayse Derya Cavga, Artem Cherkasov:
DeepCOP: deep learning-based approach to predict gene regulating effects of small molecules. Bioinform. 36(3): 813-818 (2020)
2010 – 2019
- 2019
- [j9]Michael Fernández, Fuqiang Ban, Godwin Woo, Olexandr Isayev, Carl Perez, Valery Fokin, Alexander Tropsha, Artem Cherkasov:
Quantitative Structure-Price Relationship (QS$R) Modeling and the Development of Economically Feasible Drug Discovery Projects. J. Chem. Inf. Model. 59(4): 1306-1313 (2019) - 2018
- [j8]Michael Fernández, Fuqiang Ban, Godwin Woo, Michael Hsing, Takeshi Yamazaki, Eric Leblanc, Paul S. Rennie, William J. Welch, Artem Cherkasov:
Toxic Colors: The Use of Deep Learning for Predicting Toxicity of Compounds Merely from Their Graphic Images. J. Chem. Inf. Model. 58(8): 1533-1543 (2018) - 2017
- [j7]Baichuan Sun, Michael Fernández, Amanda S. Barnard:
Machine Learning for Silver Nanoparticle Electron Transfer Property Prediction. J. Chem. Inf. Model. 57(10): 2413-2423 (2017) - 2015
- [j6]Michael Fernández, Hongqing Shi, Amanda S. Barnard:
Quantitative Structure-Property Relationship Modeling of Electronic Properties of Graphene Using Atomic Radial Distribution Function Scores. J. Chem. Inf. Model. 55(12): 2500-2506 (2015) - 2014
- [c3]Mayra Zurbarán, Karen Ávila, Pedro M. Wightman, Michael Fernández:
Near-Rand: Noise-based location obfuscation based on random neighboring points. LATINCOM 2014: 1-6 - 2011
- [j5]Michael Fernández, Yutaro Kumagai, Daron M. Standley, Akinori Sarai, Kenji Mizuguchi, Shandar Ahmad:
Prediction of dinucleotide-specific RNA-binding sites in proteins. BMC Bioinform. 12(S-13): S5 (2011) - 2010
- [j4]Michael Fernández, Shandar Ahmad, Akinori Sarai:
Proteochemometric Recognition of Stable Kinase Inhibition Complexes Using Topological Autocorrelation and Support Vector Machines. J. Chem. Inf. Model. 50(6): 1179-1188 (2010)
2000 – 2009
- 2009
- [c2]Michael Fernández, Akinori Sarai, Shandar Ahmad:
Recognition of Drug-Target Interaction Patterns using Genetic Algorithm-optimized Bayesian-regularized Neural Networks and Support Vector Machines. SMC 2009: 498-503 - 2008
- [c1]Syed Zahid Ahmed, Julien Eydoux, Michael Fernández, Laurent Rouge, Gilles Sassatelli, Lionel Torres:
Power Consumption Reduction Explorations in Processors by Enhancing Performance Using Small ESL Reprogrammable eFPGAs. ReConFig 2008: 313-318 - 2006
- [j3]Julio Caballero, Leyden Fernández, José Ignacio Abreu, Michael Fernández:
Amino Acid Sequence Autocorrelation Vectors and Ensembles of Bayesian-Regularized Genetic Neural Networks for Prediction of Conformational Stability of Human Lysozyme Mutants. J. Chem. Inf. Model. 46(3): 1255-1268 (2006) - 2005
- [j2]Julio Caballero, Miguel Garriga, Michael Fernández:
Genetic neural network modeling of the selective inhibition of the intermediate-conductance Ca2+-activated K+ channel by some triarylmethanes using topological charge indexes descriptors. J. Comput. Aided Mol. Des. 19(11): 771-789 (2005) - [j1]Michael Fernández, Alain Tundidor-Camba, Julio Caballero:
Modeling of Cyclin-Dependent Kinase Inhibition by 1H-Pyrazolo[3, 4-d]Pyrimidine Derivatives Using Artificial Neural Network Ensembles. J. Chem. Inf. Model. 45(6): 1884-1895 (2005)
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