Follow
Michael Fernandez Llamosa
Michael Fernandez Llamosa
Machine Learning Specialist
Verified email at applusrtd.com
Title
Cited by
Cited by
Year
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
7692020
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
2782021
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
2772014
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
2492021
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
2162013
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
1852022
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
1602022
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
1482013
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
1472012
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
1212011
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
1052018
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
1052005
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
1012006
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
962008
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
912016
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
882006
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
862006
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
832016
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
832008
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
782006
The system can't perform the operation now. Try again later.
Articles 1–20