Humberto González Díaz-rekin lankidetzan egindako argitalpenak (35)

2024

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

    Biomedicine and Pharmacotherapy, Vol. 174

  2. Implementation of IFPTML Computational Models in Drug Discovery Against Flaviviridae Family

    Journal of Chemical Information and Modeling, Vol. 64, Núm. 6, pp. 1841-1852

  3. MATEO: intermolecular α-amidoalkylation theoretical enantioselectivity optimization. Online tool for selection and design of chiral catalysts and products

    Journal of Cheminformatics, Vol. 16, Núm. 1

  4. Machine learning guided prediction of warfarin blood levels for personalized medicine based on clinical longitudinal data from cardiac surgery patients: a prospective observational study

    International Journal of Surgery

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

    Journal of Nanobiotechnology, Vol. 22, Núm. 1

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

    Beilstein Journal of Nanotechnology, Vol. 15, pp. 535-555

  7. OptiMo-LDLr: An Integrated In Silico Model with Enhanced Predictive Power for LDL Receptor Variants, Unraveling Hot Spot Pathogenic Residues

    Advanced Science, Vol. 11, Núm. 13

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

    Polymers, Vol. 16, Núm. 19

  9. Warfarin–A natural anticoagulant: A review of research trends for precision medication

    Phytomedicine, Vol. 128

2022

  1. Multi-output chemometrics model for gasoline compounding

    Fuel, Vol. 310

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

    Journal of chemical information and modeling, Vol. 62, Núm. 16, pp. 3928-3940

2021

  1. MLb-LDLr: A Machine Learning Model for Predicting the Pathogenicity of LDLr Missense Variants

    JACC: Basic to Translational Science, Vol. 6, Núm. 11, pp. 815-827

  2. MLb-LDLr: LDLaren hartzailearen aldaeren eragina aurresatekoikasketa automatikoko eredua

    Osasun zientzak: IV. Ikergazte Nazioarteko Ikerteta Euskaraz. 2021eko ekainaren 9, 10 eta . Gasteiz, Euskal Herria.

  3. Palladium-mediated synthesis and biological evaluation of C-10b substituted Dihydropyrrolo[1,2-b]isoquinolines as antileishmanial agents

    European Journal of Medicinal Chemistry, Vol. 220

  4. Prediction of anti-glioblastoma drug-decorated nanoparticle delivery systems using molecular descriptors and machine learning

    International Journal of Molecular Sciences, Vol. 22, Núm. 21

  5. 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

2020

  1. MCDcalc: Markov chain molecular descriptors calculator for medicinal chemistry

    Current Topics in Medicinal Chemistry, Vol. 20, Núm. 4, pp. 305-317

  2. PTML Model for Selection of Nanoparticles, Anticancer Drugs, and Vitamins in the Design of Drug-Vitamin Nanoparticle Release Systems for Cancer Cotherapy

    Molecular pharmaceutics, Vol. 17, Núm. 7, pp. 2612-2627

  3. PTML Model of ChEMBL Compounds Assays for Vitamin Derivatives

    ACS Combinatorial Science, Vol. 22, Núm. 3, pp. 129-141

  4. Perturbation-theory machine learning (PTML) multilabel model of the CheMBL dataset of preclinical assays for antisarcoma compounds

    ACS Omega, Vol. 5, Núm. 42, pp. 27211-27220