| 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 | 765 | 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 | 276 | 2014 |
| Timing of surgery following SARS‐CoV‐2 infection: an international prospective cohort study COVIDSurg Collaborative, GlobalSurg Collaborative, D Nepogodiev, ... Anaesthesia 76 (6), 748-758, 2021 | 275 | 2021 |
| Effect of COVID-19 pandemic lockdowns on planned cancer surgery for 15 tumour types in 61 countries: an international, prospective, cohort study J Glasbey, A Ademuyiwa, A Adisa, E AlAmeer, AP Arnaud, F Ayasra, ... The Lancet Oncology 22 (11), 1507-1517, 2021 | 247 | 2021 |
| 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 | 216 | 2013 |
| Artificial intelligence–enabled virtual screening of ultra-large chemical libraries with deep docking F Gentile, JC Yaacoub, J Gleave, M Fernandez, AT Ton, F Ban, A Stern, ... Nature Protocols 17 (3), 672-697, 2022 | 182 | 2022 |
| The transformational role of GPU computing and deep learning in drug discovery M Pandey, M Fernandez, F Gentile, O Isayev, A Tropsha, AC Stern, ... Nature Machine Intelligence 4 (3), 211-221, 2022 | 154 | 2022 |
| 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 | 148 | 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 | 147 | 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 | 121 | 2011 |
| 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 | 105 | 2018 |
| 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 | 105 | 2005 |
| 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 | 96 | 2008 |
| 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 | 91 | 2016 |
| 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 | 88 | 2006 |
| 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 |
| 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 | 83 | 2016 |
| Analysis of IL-10, IL-4 and TNF-α polymorphisms in drug-induced liver injury (DILI) and its outcome K Pachkoria, MI Lucena, E Crespo, F Ruiz-Cabello, S Lopez-Ortega, ... Journal of hepatology 49 (1), 107-114, 2008 | 83 | 2008 |
| 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 | 78 | 2006 |
