Lista de obras - Michael Fernandez - Dominio Público Uruguay

2D Autocorrelation modeling of the negative inotropic activity of calcium entry blockers using Bayesian-regularized genetic neural networks.

artículo científico publicado en 2006

2D Autocorrelation, CoMFA, and CoMSIA modeling of protein tyrosine kinases' inhibition by substituted pyrido[2,3-d]pyrimidine derivatives.

artículo científico publicado en 2007

2D autocorrelation modelling of the inhibitory activity of cytokinin-derived cyclin-dependent kinase inhibitors.

artículo científico publicado en 2006

A CoMSIA study on the adenosine kinase inhibition of pyrrolo[2,3-d]pyrimidine nucleoside analogues.

artículo científico publicado en 2008

Analysis of Aurora kinase A expression in CD34(+) blast cells isolated from patients with myelodysplastic syndromes and acute myeloid leukemia

artículo científico publicado en 2008

Artificial neural network analysis of the catalytic efficiency of platinum nanoparticles

scholarly article by Michael Fernandez et al published 2017 in RSC Advances

Artificial neural networks from MATLAB in medicinal chemistry. Bayesian-regularized genetic neural networks (BRGNN): application to the prediction of the antagonistic activity against human platelet thrombin receptor (PAR-1).

artículo científico publicado en 2008

Bayesian-regularized genetic neural networks applied to the modeling of non-peptide antagonists for the human luteinizing hormone-releasing hormone receptor.

artículo científico publicado en 2006

Docking and quantitative structure-activity relationship studies for sulfonyl hydrazides as inhibitors of cytosolic human branched-chain amino acid aminotransferase

artículo científico publicado en 2009

Effects of beta-cyclodextrin-dextran polymer on stability properties of trypsin

artículo científico publicado en 2003

Genetic neural network modeling of the selective inhibition of the intermediate-conductance Ca2+ -activated K+ channel by some triarylmethanes using topological charge indexes descriptors.

artículo científico publicado en 2005

Genome-wide enhancer prediction from epigenetic signatures using genetic algorithm-optimized support vector machines.

artículo científico publicado en 2012

Geometrical Properties Can Predict CO2 and N2 Adsorption Performance of Metal-Organic Frameworks (MOFs) at Low Pressure

artículo científico publicado en 2016

Geometrical features can predict electronic properties of graphene nanoflakes

scholarly article in Carbon, vol. 103, July 2016

HDM4 (HDMX) is widely expressed in adult pre-B acute lymphoblastic leukemia and is a potential therapeutic target

artículo científico publicado en 2006

Identification of Nanoparticle Prototypes and Archetypes

artículo científico publicado en 2015

Impact of distributions on the archetypes and prototypes in heterogeneous nanoparticle ensembles.

artículo científico publicado en 2016

Linear and nonlinear QSAR study of N-hydroxy-2-[(phenylsulfonyl)amino]acetamide derivatives as matrix metalloproteinase inhibitors.

artículo científico publicado en 2006

Linear and nonlinear modeling of antifungal activity of some heterocyclic ring derivatives using multiple linear regression and Bayesian-regularized neural networks.

artículo científico publicado en 2005

Machine learning and genetic algorithm prediction of energy differences between electronic calculations of graphene nanoflakes

artículo científico publicado en 2017

Modeling corrosion inhibition efficacy of small organic molecules as non-toxic chromate alternatives using comparative molecular surface analysis (CoMSA).

artículo científico publicado en 2016

Modeling of cyclin-dependent kinase inhibition by 1H-pyrazolo[3,4-d]pyrimidine derivatives using artificial neural network ensembles.

artículo científico publicado en 2005

Modeling of farnesyltransferase inhibition by some thiol and non-thiol peptidomimetic inhibitors using genetic neural networks and RDF approaches.

artículo científico

Prediction of dinucleotide-specific RNA-binding sites in proteins

artículo científico publicado en 2011

Proteochemometric recognition of stable kinase inhibition complexes using topological autocorrelation and support vector machines

artículo científico publicado en 2010

QSAR Accelerated Discovery of Potent Ice Recrystallization Inhibitors.

artículo científico publicado en 2016

QSAR modeling of matrix metalloproteinase inhibition by N-hydroxy-alpha-phenylsulfonylacetamide derivatives.

artículo científico publicado en 2007

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

artículo científico publicado en 2015

Quantitative Structure–Activity Relationship of Organosulphur Compounds as Soybean 15‐Lipoxygenase Inhibitors Using CoMFA and CoMSIA ⬇️

artículo científico publicado el 11 de octubre de 2010

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

artículo científico publicado en 2019

Quantitative structure-activity relationship modeling of growth hormone secretagogues agonist activity of some tetrahydroisoquinoline 1-carboxamides.

artículo científico publicado en 2007

Quantitative structure-activity relationship of rubiscolin analogues as delta opioid peptides using comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA).

artículo científico publicado en 2007

Quantitative structure-activity relationship to predict differential inhibition of aldose reductase by flavonoid compounds

artículo científico publicado en 2005

Rapid and Accurate Machine Learning Recognition of High Performing Metal Organic Frameworks for CO2 Capture.

artículo científico publicado en 2014

Recognition of drug-target interaction patterns using genetic algorithm-optimized Bayesian-regularized neural networks and support vector machines

Small molecule-induced degradation of the full length and V7 truncated variant forms of human androgen receptor

scientific article published on 24 August 2018

Statistics, damned statistics and nanoscience – using data science to meet the challenge of nanomaterial complexity

scientific article published on 05 February 2016

The Addition of All-Trans Retinoic Acid to Chemotherapy May Not Improve the Outcome of Patient with NPM1 Mutated Acute Myeloid Leukemia

artículo científico publicado en 2013

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

artículo científico publicado en 2018

Transglutaminase-catalyzed synthesis of trypsin-cyclodextrin conjugates: kinetics and stability properties.

artículo científico publicado en 2003

Lista de obras de Michael Fernandez

2D Autocorrelation modeling of the negative inotropic activity of calcium entry blockers using Bayesian-regularized genetic neural networks.

2D Autocorrelation, CoMFA, and CoMSIA modeling of protein tyrosine kinases' inhibition by substituted pyrido[2,3-d]pyrimidine derivatives.

2D autocorrelation modelling of the inhibitory activity of cytokinin-derived cyclin-dependent kinase inhibitors.

A CoMSIA study on the adenosine kinase inhibition of pyrrolo[2,3-d]pyrimidine nucleoside analogues.

Analysis of Aurora kinase A expression in CD34(+) blast cells isolated from patients with myelodysplastic syndromes and acute myeloid leukemia

Artificial neural network analysis of the catalytic efficiency of platinum nanoparticles

Artificial neural networks from MATLAB in medicinal chemistry. Bayesian-regularized genetic neural networks (BRGNN): application to the prediction of the antagonistic activity against human platelet thrombin receptor (PAR-1).

Bayesian-regularized genetic neural networks applied to the modeling of non-peptide antagonists for the human luteinizing hormone-releasing hormone receptor.

Docking and quantitative structure-activity relationship studies for sulfonyl hydrazides as inhibitors of cytosolic human branched-chain amino acid aminotransferase

Effects of beta-cyclodextrin-dextran polymer on stability properties of trypsin

Genetic neural network modeling of the selective inhibition of the intermediate-conductance Ca2+ -activated K+ channel by some triarylmethanes using topological charge indexes descriptors.

Genome-wide enhancer prediction from epigenetic signatures using genetic algorithm-optimized support vector machines.

Geometrical Properties Can Predict CO2 and N2 Adsorption Performance of Metal-Organic Frameworks (MOFs) at Low Pressure

Geometrical features can predict electronic properties of graphene nanoflakes

HDM4 (HDMX) is widely expressed in adult pre-B acute lymphoblastic leukemia and is a potential therapeutic target

Identification of Nanoparticle Prototypes and Archetypes

Impact of distributions on the archetypes and prototypes in heterogeneous nanoparticle ensembles.

Linear and nonlinear QSAR study of N-hydroxy-2-[(phenylsulfonyl)amino]acetamide derivatives as matrix metalloproteinase inhibitors.

Linear and nonlinear modeling of antifungal activity of some heterocyclic ring derivatives using multiple linear regression and Bayesian-regularized neural networks.

Machine learning and genetic algorithm prediction of energy differences between electronic calculations of graphene nanoflakes

Modeling corrosion inhibition efficacy of small organic molecules as non-toxic chromate alternatives using comparative molecular surface analysis (CoMSA).

Modeling of cyclin-dependent kinase inhibition by 1H-pyrazolo[3,4-d]pyrimidine derivatives using artificial neural network ensembles.

Modeling of farnesyltransferase inhibition by some thiol and non-thiol peptidomimetic inhibitors using genetic neural networks and RDF approaches.

Prediction of dinucleotide-specific RNA-binding sites in proteins

Proteochemometric recognition of stable kinase inhibition complexes using topological autocorrelation and support vector machines

QSAR Accelerated Discovery of Potent Ice Recrystallization Inhibitors.

QSAR modeling of matrix metalloproteinase inhibition by N-hydroxy-alpha-phenylsulfonylacetamide derivatives.

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

Quantitative Structure–Activity Relationship of Organosulphur Compounds as Soybean 15‐Lipoxygenase Inhibitors Using CoMFA and CoMSIA ⬇️

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

Quantitative structure-activity relationship modeling of growth hormone secretagogues agonist activity of some tetrahydroisoquinoline 1-carboxamides.

Quantitative structure-activity relationship of rubiscolin analogues as delta opioid peptides using comparative molecular field analysis (CoMFA) and comparative molecular similarity indices analysis (CoMSIA).

Quantitative structure-activity relationship to predict differential inhibition of aldose reductase by flavonoid compounds

Rapid and Accurate Machine Learning Recognition of High Performing Metal Organic Frameworks for CO2 Capture.

Recognition of drug-target interaction patterns using genetic algorithm-optimized Bayesian-regularized neural networks and support vector machines

Small molecule-induced degradation of the full length and V7 truncated variant forms of human androgen receptor

Statistics, damned statistics and nanoscience – using data science to meet the challenge of nanomaterial complexity

The Addition of All-Trans Retinoic Acid to Chemotherapy May Not Improve the Outcome of Patient with NPM1 Mutated Acute Myeloid Leukemia

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

Transglutaminase-catalyzed synthesis of trypsin-cyclodextrin conjugates: kinetics and stability properties.