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New Experimental and Computational Tools for Drug Discovery. Part – XII

Current topics in medicinal chemistry, 2021-04, Vol.21 (9), p.789-789

González-Díaz, Humberto

2021

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New Experimental and Computational Tools for Drug Discovery: Part - XI

Current topics in medicinal chemistry, 2021-01, Vol.21 (7), p.597-598

González-Díaz, Humberto

2021

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IFPTML mapping of nanoparticle antibacterial activity vs. pathogen metabolic networks

Nanoscale, 2021-01, Vol.13 (2), p.1318-1330

2021

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Multi-Endpoint Acute Toxicity Assessment of Organic Compounds Using Large-Scale Machine Learning Modeling

Environmental science & technology, 2024-06, Vol.58 (23), p.10116-10127

2024

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Proteomics, networks and connectivity indices

Proteomics (Weinheim), 2008-02, Vol.8 (4), p.750-778

2008

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Implementation of IFPTML Computational Models in Drug Discovery Against Flaviviridae Family

Journal of chemical information and modeling, 2024-03, Vol.64 (6), p.1841-1852

2024

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Computational Tool for Risk Assessment of Nanomaterials: Novel QSTR-Perturbation Model for Simultaneous Prediction of Ecotoxicity and Cytotoxicity of Uncoated and Coated Nanoparticles under Multiple Experimental Conditions

Environmental science & technology, 2014-12, Vol.48 (24), p.14686-14694

2014

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Perturbation-Theory and Machine Learning (PTML) Model for High-Throughput Screening of Parham Reactions: Experimental and Theoretical Studies

Journal of chemical information and modeling, 2018-07, Vol.58 (7), p.1384-1396

2018

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IFPTML Mapping of Drug Graphs with Protein and Chromosome Structural Networks vs. Pre-Clinical Assay Information for Discovery of Antimalarial Compounds

International journal of molecular sciences, 2021-12, Vol.22 (23), p.13066

2021

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Medicinal chemistry and bioinformatics--current trends in drugs discovery with networks topological indices

Current topics in medicinal chemistry, 2007-05, Vol.7 (10), p.1015-1029

2007

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Computational ecotoxicology: Simultaneous prediction of ecotoxic effects of nanoparticles under different experimental conditions

Environment international, 2014-12, Vol.73 (C), p.288-294

2014

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Prediction of Antileishmanial Compounds: General Model, Preparation, and Evaluation of 2‑Acylpyrrole Derivatives

Journal of chemical information and modeling, 2022-08, Vol.62 (16), p.3928-3940

2022

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Predicting antimicrobial drugs and targets with the MARCH-INSIDE approach

Current topics in medicinal chemistry, 2008-12, Vol.8 (18), p.1676-1690

2008

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Alignment-Free Prediction of a Drug−Target Complex Network Based on Parameters of Drug Connectivity and Protein Sequence of Receptors

Molecular pharmaceutics, 2009-06, Vol.6 (3), p.825-835

2009

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Predicting Metabolic Reaction Networks with Perturbation-Theory Machine Learning (PTML) Models

Current topics in medicinal chemistry, 2021-04, Vol.21 (9), p.819-827

2021

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General theory for multiple input-output perturbations in complex molecular systems. 1. Linear QSPR electronegativity models in physical, organic, and medicinal chemistry

Current topics in medicinal chemistry, 2013-07, Vol.13 (14), p.1713-1741

2013

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On the additive artificial intelligence-based discovery of nanoparticle neurodegenerative disease drug delivery systems

Beilstein journal of nanotechnology, 2024-05, Vol.15 (1), p.535-555

2024

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ANN Multiscale Model of Anti-HIV Drugs Activity vs AIDS Prevalence in the US at County Level Based on Information Indices of Molecular Graphs and Social Networks

Journal of chemical information and modeling, 2014-03, Vol.54 (3), p.744-755

2014

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Prediction of Dielectric Constant in Series of Polymers by Quantitative Structure-Property Relationship (QSPR)

Polymers, 2024-09, Vol.16 (19), p.2731

2024

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Computational chemistry study of 3D-structure-function relationships for enzymes based on Markov models for protein electrostatic, HINT, and van der Waals potentials

Journal of computational chemistry, 2009-07, Vol.30 (9), p.1510-1520

2009

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Experimental–Computational Study of Carbon Nanotube Effects on Mitochondrial Respiration: In Silico Nano-QSPR Machine Learning Models Based on New Raman Spectra Transform with Markov–Shannon Entropy Invariants

Journal of chemical information and modeling, 2017-05, Vol.57 (5), p.1029-1044

2017

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Quantitative Structure−Activity Relationship and Complex Network Approach to Monoamine Oxidase A and B Inhibitors

Journal of medicinal chemistry, 2008-11, Vol.51 (21), p.6740-6751

2008

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Unified QSAR and network-based computational chemistry approach to antimicrobials, part 1: Multispecies activity models for antifungals

Journal of computational chemistry, 2008-03, Vol.29 (4), p.656-667

2008

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Identification of Riluzole derivatives as novel calmodulin inhibitors with neuroprotective activity by a joint synthesis, biosensor, and computational guided strategy

Biomedicine & pharmacotherapy, 2024-05, Vol.174, p.116602, Article 116602

2024

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NANO.PTML model for read-across prediction of nanosystems in neurosciences. computational model and experimental case of study

Journal of nanobiotechnology, 2024-07, Vol.22 (1), p.435-19, Article 435

2024

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New Experimental and Computational Tools for Drug Discovery. Part – XII

New Experimental and Computational Tools for Drug Discovery: Part - XI

IFPTML mapping of nanoparticle antibacterial activity vs. pathogen metabolic networks

Multi-Endpoint Acute Toxicity Assessment of Organic Compounds Using Large-Scale Machine Learning Modeling

Proteomics, networks and connectivity indices

Implementation of IFPTML Computational Models in Drug Discovery Against Flaviviridae Family

Computational Tool for Risk Assessment of Nanomaterials: Novel QSTR-Perturbation Model for Simultaneous Prediction of Ecotoxicity and Cytotoxicity of Uncoated and Coated Nanoparticles under Multiple Experimental Conditions

Perturbation-Theory and Machine Learning (PTML) Model for High-Throughput Screening of Parham Reactions: Experimental and Theoretical Studies

IFPTML Mapping of Drug Graphs with Protein and Chromosome Structural Networks vs. Pre-Clinical Assay Information for Discovery of Antimalarial Compounds

Medicinal chemistry and bioinformatics--current trends in drugs discovery with networks topological indices

Computational ecotoxicology: Simultaneous prediction of ecotoxic effects of nanoparticles under different experimental conditions

Prediction of Antileishmanial Compounds: General Model, Preparation, and Evaluation of 2‑Acylpyrrole Derivatives

Predicting antimicrobial drugs and targets with the MARCH-INSIDE approach

Alignment-Free Prediction of a Drug−Target Complex Network Based on Parameters of Drug Connectivity and Protein Sequence of Receptors

Predicting Metabolic Reaction Networks with Perturbation-Theory Machine Learning (PTML) Models

General theory for multiple input-output perturbations in complex molecular systems. 1. Linear QSPR electronegativity models in physical, organic, and medicinal chemistry

On the additive artificial intelligence-based discovery of nanoparticle neurodegenerative disease drug delivery systems

ANN Multiscale Model of Anti-HIV Drugs Activity vs AIDS Prevalence in the US at County Level Based on Information Indices of Molecular Graphs and Social Networks

Prediction of Dielectric Constant in Series of Polymers by Quantitative Structure-Property Relationship (QSPR)

Computational chemistry study of 3D-structure-function relationships for enzymes based on Markov models for protein electrostatic, HINT, and van der Waals potentials

Experimental–Computational Study of Carbon Nanotube Effects on Mitochondrial Respiration: In Silico Nano-QSPR Machine Learning Models Based on New Raman Spectra Transform with Markov–Shannon Entropy Invariants

Quantitative Structure−Activity Relationship and Complex Network Approach to Monoamine Oxidase A and B Inhibitors

Unified QSAR and network-based computational chemistry approach to antimicrobials, part 1: Multispecies activity models for antifungals

Identification of Riluzole derivatives as novel calmodulin inhibitors with neuroprotective activity by a joint synthesis, biosensor, and computational guided strategy

NANO.PTML model for read-across prediction of nanosystems in neurosciences. computational model and experimental case of study

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