HUMBERTO
GONZALEZ DIAZ
VISITANTE IKERBASQUE
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Universidade de Santiago de Compostela
Santiago de Compostela, EspañaPublikationen in Zusammenarbeit mit Forschern von Universidade de Santiago de Compostela (153)
2023
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Trends in Nanoparticles for Leishmania Treatment: A Bibliometric and Network Analysis
Diseases, Vol. 11, Núm. 4
2021
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Synthesis, Pharmacological, and Biological Evaluation of 2-Furoyl-Based MIF-1 Peptidomimetics and the Development of a General-Purpose Model for Allosteric Modulators (ALLOPTML)
ACS Chemical Neuroscience, Vol. 12, Núm. 1, pp. 203-215
2019
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Perturbation Theory Machine Learning Modeling of Immunotoxicity for Drugs Targeting Inflammatory Cytokines and Study of the Antimicrobial G1 Using Cytometric Bead Arrays
Chemical Research in Toxicology, Vol. 32, Núm. 9, pp. 1811-1823
2018
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Perturbation Theory/Machine Learning Model of ChEMBL Data for Dopamine Targets: Docking, Synthesis, and Assay of New l -Prolyl- l -leucyl-glycinamide Peptidomimetics
ACS Chemical Neuroscience, Vol. 9, Núm. 11, pp. 2572-2587
2017
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A study of the Immune Epitope Database for some fungi species using network topological indices
Molecular Diversity, Vol. 21, Núm. 3, pp. 713-718
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Multi-target mining of alzheimer disease proteome with Hansch’s QSBR-perturbation theory and experimental-theoretic study of new thiophene isosters of rasagiline
Current Drug Targets, Vol. 18, Núm. 5, pp. 511-521
2016
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Computational modeling and experimental facts of mixed self-assembly systems
Current Pharmaceutical Design, Vol. 22, Núm. 34, pp. 5249-5256
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Experimental-theoretic approach to drug-lymphocyte interactome networks with flow cytometry and spectral moments perturbation theory
Current Pharmaceutical Design, Vol. 22, Núm. 33, pp. 5114-5119
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QSPR-Perturbation Models for the Prediction of B-Epitopes from Immune Epitope Database: A Potentially Valuable Route for Predicting “In Silico” New Optimal Peptide Sequences and/or Boundary Conditions for Vaccine Development
International Journal of Peptide Research and Therapeutics, Vol. 22, Núm. 4, pp. 445-450
2015
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Bio-AIMS collection of chemoinformatics web tools based on molecular graph information and Artificial Intelligence Models
Combinatorial Chemistry and High Throughput Screening, Vol. 18, Núm. 8, pp. 735-750
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MI-NODES multiscale models of metabolic reactions, brain connectome, ecological, epidemic, world trade, and legal-social networks
Current Bioinformatics, Vol. 10, Núm. 5, pp. 692-713
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MIANN models of networks of biochemical reactions, ecosystems, and U.S. supreme court with Balaban-Markov indices
Current Bioinformatics, Vol. 10, Núm. 5, pp. 658-671
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Mapping chemical structure-activity information of HAART-drug cocktails over complex networks of AIDS epidemiology and socioeconomic data of U.S. counties
BioSystems, Vol. 132-133, pp. 20-34
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Multiscale mapping of AIDS in U.S. countries vs anti-HIV drugs activity with complex networks and information indices
Current Bioinformatics, Vol. 10, Núm. 5, pp. 639-657
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Self-Assembled Binary Nanoscale Systems: Multioutput Model with LFER-Covariance Perturbation Theory and an Experimental-Computational Study of NaGDC-DDAB Micelles
Langmuir, Vol. 31, Núm. 44, pp. 12009-12018
2014
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A QSPR-like model for multilocus genotype networks of Fasciola hepatica in Northwest Spain
Journal of Theoretical Biology, Vol. 343, pp. 16-24
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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, Vol. 54, Núm. 3, pp. 744-755
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Computational ecotoxicology: Simultaneous prediction of ecotoxic effects of nanoparticles under different experimental conditions
Environment International, Vol. 73, pp. 288-294
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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 and Technology, Vol. 48, Núm. 24, pp. 14686-14694
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Computer-aided nanotoxicology: Assessing cytotoxicity of nanoparticles under diverse experimental conditions by using a novel QSTR-perturbation approach
Nanoscale, Vol. 6, Núm. 18, pp. 10623-10630