| The value of antimicrobial peptides in the age of resistance M Magana, M Pushpanathan, AL Santos, L Leanse, M Fernandez, ... The Lancet Infectious Diseases 20 (9), e216-e230, 2020 | 481 | 2020 |
| Rapid and Accurate Machine Learning Recognition of High Performing Metal Organic Frameworks for CO2 Capture M Fernandez, PG Boyd, TD Daff, MZ Aghaji, TK Woo The journal of physical chemistry letters 5 (17), 3056-3060, 2014 | 230 | 2014 |
| Large-scale quantitative structure–property relationship (QSPR) analysis of methane storage in metal–organic frameworks M Fernandez, TK Woo, CE Wilmer, RQ Snurr The Journal of Physical Chemistry C 117 (15), 7681-7689, 2013 | 170 | 2013 |
| Genome-wide enhancer prediction from epigenetic signatures using genetic algorithm-optimized support vector machines M Fernandez, D Miranda-Saavedra Nucleic acids research 40 (10), e77-e77, 2012 | 137 | 2012 |
| Genetic algorithm optimization in drug design QSAR: Bayesian-regularized genetic neural networks (BRGNN) and genetic algorithm-optimized support vectors machines (GA-SVM) M Fernandez, J Caballero, L Fernandez, A Sarai Molecular diversity 15, 269-289, 2011 | 110 | 2011 |
| Quantitative structure–activity relationship to predict differential inhibition of aldose reductase by flavonoid compounds M Fernández, J Caballero, AM Helguera, EA Castro, MP González Bioorganic & medicinal chemistry 13 (9), 3269-3277, 2005 | 107 | 2005 |
| Atomic property weighted radial distribution functions descriptors of metal–organic frameworks for the prediction of gas uptake capacity M Fernandez, NR Trefiak, TK Woo The Journal of Physical Chemistry C 117 (27), 14095-14105, 2013 | 106 | 2013 |
| QSAR for non-nucleoside inhibitors of HIV-1 reverse transcriptase PR Duchowicz, M Fernández, J Caballero, EA Castro, FM Fernández Bioorganic & medicinal chemistry 14 (17), 5876-5889, 2006 | 101 | 2006 |
| Artificial neural networks from MATLAB® in medicinal chemistry. Bayesian-regularized genetic neural networks (BRGNN): Application to the prediction of the antagonistic activity … J Caballero, M Fernández Current topics in medicinal chemistry 8 (18), 1580-1605, 2008 | 92 | 2008 |
| Linear and nonlinear modeling of antifungal activity of some heterocyclic ring derivatives using multiple linear regression and Bayesian-regularized neural networks J Caballero, M Fernández Journal of Molecular Modeling 12, 168-181, 2006 | 86 | 2006 |
| Toxic colors: the use of deep learning for predicting toxicity of compounds merely from their graphic images M Fernandez, F Ban, G Woo, M Hsing, T Yamazaki, E LeBlanc, ... Journal of chemical information and modeling 58 (8), 1533-1543, 2018 | 84 | 2018 |
| Linear and nonlinear QSAR study of N-hydroxy-2-[(phenylsulfonyl) amino] acetamide derivatives as matrix metalloproteinase inhibitors M Fernández, J Caballero, A Tundidor-Camba Bioorganic & medicinal chemistry 14 (12), 4137-4150, 2006 | 82 | 2006 |
| Modeling of activity of cyclic urea HIV-1 protease inhibitors using regularized-artificial neural networks M Fernández, J Caballero Bioorganic & medicinal chemistry 14 (1), 280-294, 2006 | 76 | 2006 |
| Geometrical Properties Can Predict CO2 and N2 Adsorption Performance of Metal–Organic Frameworks (MOFs) at Low Pressure M Fernandez, AS Barnard acs combinatorial science 18 (5), 243-252, 2016 | 73 | 2016 |
| Amino Acid Sequence Autocorrelation vectors and ensembles of Bayesian-Regularized Genetic Neural Networks for prediction of conformational stability of human lysozyme mutants J Caballero, L Fernandez, JI Abreu, M Fernández Journal of chemical information and modeling 46 (3), 1255-1268, 2006 | 69 | 2006 |
| Proteometric study of ghrelin receptor function variations upon mutations using amino acid sequence autocorrelation vectors and genetic algorithm-based least square support … J Caballero, L Fernández, M Garriga, JI Abreu, S Collina, M Fernández Journal of Molecular Graphics and Modelling 26 (1), 166-178, 2007 | 67 | 2007 |
| Transglutaminase‐catalyzed synthesis of trypsin–cyclodextrin conjugates: Kinetics and stability properties R Villalonga, M Fernandez, A Fragoso, R Cao, P Di Pierro, L Mariniello, ... Biotechnology and bioengineering 81 (6), 732-737, 2003 | 67 | 2003 |
| Modeling of cyclin-dependent kinase inhibition by 1 H-pyrazolo [3, 4-d] pyrimidine derivatives using artificial neural network ensembles M Fernandez, A Tundidor-Camba, J Caballero Journal of chemical information and modeling 45 (6), 1884-1895, 2005 | 66 | 2005 |
| Quantitative structure–property relationship models for recognizing metal organic frameworks (MOFs) with high CO2 working capacity and CO2/CH4 selectivity for methane purification MZ Aghaji, M Fernandez, PG Boyd, TD Daff, TK Woo European Journal of Inorganic Chemistry 2016 (27), 4505-4511, 2016 | 65 | 2016 |
| Modeling of farnesyltransferase inhibition by some thiol and non-thiol peptidomimetic inhibitors using genetic neural networks and RDF approaches MP González, J Caballero, A Tundidor-Camba, AM Helguera, ... Bioorganic & medicinal chemistry 14 (1), 200-213, 2006 | 63 | 2006 |
