Publicaciones en colaboración con investigadores/as de Universidad del País Vasco/Euskal Herriko Unibertsitatea (36)

2024

  1. A Novel Protocol Using Captive Portals for FIDO2 Network Authentication †

    Applied Sciences (Switzerland), Vol. 14, Núm. 9

  2. From molecular mechanisms of prostate cancer to translational applications: based on multi-omics fusion analysis and intelligent medicine

    Health Information Science and Systems, Vol. 12, Núm. 1

  3. Unraveling druggable cancer-driving proteins and targeted drugs using artificial intelligence and multi-omics analyses

    Scientific Reports, Vol. 14, Núm. 1

2023

  1. Adapting a Captive Portal for Phishing-Resistant Network Authentication Using Security Keys

    2023 JNIC Cybersecurity Conference, JNIC 2023

  2. Operating System Fingerprinting Tool Based on Classical Machine Learning Algorithms

    2023 JNIC Cybersecurity Conference, JNIC 2023

2021

  1. An Analysis of the Current Implementations Based on the WebAuthn and FIDO Authentication Standards †

    Engineering Proceedings, Vol. 7, Núm. 1

  2. Applying Artificial Intelligence for Operating System Fingerprinting †

    Engineering Proceedings, Vol. 7, Núm. 1

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

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

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

    Scientific Reports, Vol. 10, Núm. 1

  5. 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

  6. 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

2018

  1. Gene prioritization, communality analysis, networking and metabolic integrated pathway to better understand breast cancer pathogenesis

    Scientific Reports, Vol. 8, Núm. 1

  2. Net-Net Auto Machine Learning (AutoML) Prediction of Complex Ecosystems

    Scientific Reports, Vol. 8, Núm. 1

  3. 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

  1. Carbon nanotubes’ effect on mitochondrial oxygen flux dynamics: Polarography experimental study and machine learning models using star graph trace invariants of raman spectra

    Nanomaterials, Vol. 7, Núm. 11

  2. Decrypting Strong and Weak Single-Walled Carbon Nanotubes Interactions with Mitochondrial Voltage-Dependent Anion Channels Using Molecular Docking and Perturbation Theory

    Scientific Reports, Vol. 7, Núm. 1

  3. Experimental study and ANN dual-time scale perturbation model of electrokinetic properties of microbiota

    Frontiers in Microbiology, Vol. 8, Núm. JUN

  4. Experimental study and Random Forest prediction model of microbiome cell surface hydrophobicity

    Expert Systems with Applications, Vol. 72, pp. 306-316