about
Markovian chemicals "in silico" design (MARCH-INSIDE), a promising approach for computer-aided molecular design I: discovery of anticancer compounds.3D-chiral atom, atom-type, and total non-stochastic and stochastic molecular linear indices and their applications to central chirality codification.Atom-based 3D-chiral quadratic indices. Part 2: prediction of the corticosteroid-binding globulinbinding affinity of the 31 benchmark steroids data set.Atom-based stochastic and non-stochastic 3D-chiral bilinear indices and their applications to central chirality codification.Bond-based 3D-chiral linear indices: theory and QSAR applications to central chirality codification.Estimation of ADME properties in drug discovery: predicting Caco-2 cell permeability using atom-based stochastic and non-stochastic linear indices.A review of QSAR studies to discover new drug-like compounds actives against leishmaniasis and trypanosomiasis.A Simple Method to Predict Blood-Brain Barrier Permeability of Drug-Like Compounds Using Classification Trees.Prediction of acute toxicity of phenol derivatives using multiple linear regression approach for Tetrahymena pyriformis contaminant identification in a median-size database.Identification in silico and in vitro of novel trypanosomicidal drug-like compounds.Bond-based bilinear indices for computational discovery of novel trypanosomicidal drug-like compounds through virtual screening.Bond-based linear indices of the non-stochastic and stochastic edge-adjacency matrix. 1. Theory and modeling of ChemPhys properties of organic molecules.Computational discovery of novel trypanosomicidal drug-like chemicals by using bond-based non-stochastic and stochastic quadratic maps and linear discriminant analysis.Atom, atom-type and total molecular linear indices as a promising approach for bioorganic and medicinal chemistry: theoretical and experimental assessment of a novel method for virtual screening and rational design of new lead anthelmintic.Machine learning-based models to predict modes of toxic action of phenols to Tetrahymena pyriformis.Comparative study to predict toxic modes of action of phenols from molecular structures.Protein linear indices of the 'macromolecular pseudograph alpha-carbon atom adjacency matrix' in bioinformatics. Part 1: prediction of protein stability effects of a complete set of alanine substitutions in Arc repressor.Linear indices of the 'macromolecular graph's nucleotides adjacency matrix' as a promising approach for bioinformatics studies. Part 1: prediction of paromomycin's affinity constant with HIV-1 psi-RNA packaging region.A novel approach to predict aquatic toxicity from molecular structure.Learning from Multiple Classifier Systems: Perspectives for Improving Decision Making of QSAR Models in Medicinal Chemistry.Prediction of aquatic toxicity of benzene derivatives using molecular descriptor from atomic weighted vectors.Discrete Fourier Transform-Based Multivariate Image Analysis: Application to Modeling of Aromatase Inhibitory Activity.Prediction of Aquatic Toxicity of Benzene Derivatives to Tetrahymena pyriformis According to OECD Principles.Ligand-based discovery of novel trypanosomicidal drug-like compounds: in silico identification and experimental support.Predicting antitrichomonal activity: a computational screening using atom-based bilinear indices and experimental proofs.Dry selection and wet evaluation for the rational discovery of new anthelminticsPrediction of Caco-2 Cell Permeability Using Bilinear Indices and Multiple Linear RegressionIn silicoAntibacterial Activity Modeling Based on the TOMOCOMD-CARDD Approach3D-chiral (2.5) atom-based TOMOCOMD-CARDD descriptors: theory and QSAR applications to central chirality codificationAtom-based non-stochastic and stochastic bilinear indices: Application to QSPR/QSAR studies of organic compoundsTomocomd-Cardd, a novel approach for computer-aided ? rational? drug design: I. Theoretical and experimental assessment of a promising method for computational screening and in silico design of new anthelmintic compoundsAn approach to identify new antihypertensive agents using Thermolysin as model: In silico study based on QSARINS and docking
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P50
description
hulumtues
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researcher
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հետազոտող
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Juan A Castillo-Garit
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Juan A Castillo-Garit
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Juan A Castillo-Garit
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Juan A Castillo-Garit
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Juan A Castillo-Garit
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type
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Juan A Castillo-Garit
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Juan A Castillo-Garit
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Juan A Castillo-Garit
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Juan A Castillo-Garit
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Juan A. Castillo
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Juan A Castillo-Garit
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Juan A Castillo-Garit
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Juan A Castillo-Garit
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Juan A Castillo-Garit
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Juan A Castillo-Garit
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P1053
J-1648-2015
P106
P1153
7801470655
P2038
Juan_Castillo-Garit
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P3829
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0000-0003-0896-9484