Publicacións en colaboración con investigadores/as de Ikerbasque, Fundación Vasca para la Ciencia (45)

2024

  1. 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

  2. Minimal information for studies of extracellular vesicles (MISEV2023): From basic to advanced approaches

    Journal of Extracellular Vesicles, Vol. 13, Núm. 2

  3. Structure of graphene oxide-phospholipid monolayers: A grazing incidence X-ray diffraction and neutron and X-ray reflectivity study

    Journal of Colloid and Interface Science, Vol. 655, pp. 664-675

2023

  1. Surfactant Layers on Gold Nanorods

    Accounts of Chemical Research, Vol. 56, Núm. 10, pp. 1204-1212

2022

  1. New Insights into the Exploitation of BODIPY Derivatives as Organic Photocatalysts

    European Journal of Organic Chemistry, Vol. 2022, Núm. 39

2021

  1. Guidelines for the use and interpretation of assays for monitoring autophagy (4th edition)1

    Autophagy, Vol. 17, Núm. 1, pp. 1-382

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

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

2020

  1. A multi-objective approach for anti-osteosarcoma cancer agents discovery through drug repurposing

    Pharmaceuticals, Vol. 13, Núm. 11, pp. 1-16

  2. Gene prioritization through consensus strategy, enrichment methodologies analysis, and networking for osteosarcoma pathogenesis

    International Journal of Molecular Sciences, Vol. 21, Núm. 3

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

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

  4. Net-net autoML selection of artificial neural network topology for brain connectome prediction

    Applied Sciences (Switzerland), Vol. 10, Núm. 4

  5. OncoOmics approaches to reveal essential genes in breast cancer: a panoramic view from pathogenesis to precision medicine

    Scientific Reports, Vol. 10, Núm. 1

  6. 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

  7. Plasmonic Nanoparticles with Supramolecular Recognition

    Advanced Functional Materials, Vol. 30, Núm. 2

  8. Prediction of antimalarial drug-decorated nanoparticle delivery systems with random forest models

    Biology, Vol. 9, Núm. 8, pp. 1-15

  9. Prediction of breast cancer proteins involved in immunotherapy, metastasis, and RNA-binding using molecular descriptors and artificial neural networks

    Scientific Reports, Vol. 10, Núm. 1

  10. Ptml multi-label algorithms: Models, software, and applications

    Current Topics in Medicinal Chemistry, Vol. 20, Núm. 25, pp. 2326-2337

  11. Reversible Control of Protein Corona Formation on Gold Nanoparticles Using Host-Guest Interactions

    ACS Nano, Vol. 14, Núm. 5, pp. 5382-5391

2019

  1. PTML Model of Enzyme Subclasses for Mining the Proteome of Biofuel Producing Microorganisms

    Journal of Proteome Research, Vol. 18, Núm. 7, pp. 2735-2746

  2. 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