Publicacións en colaboración con investigadores/as de Ikerbasque, Fundación Vasca para la Ciencia (30)

2024

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

    Scientific Reports, Vol. 14, 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

2016

  1. Data analysis in chemistry and bio-medical sciences

    International Journal of Molecular Sciences

  2. Experimental and chemometric studies of cell membrane permeability

    Chemometrics and Intelligent Laboratory Systems, Vol. 154, pp. 1-6

2015

  1. 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

  2. Experimental and computational studies of fatty acid distribution networks

    Molecular BioSystems, Vol. 11, Núm. 11, pp. 2964-2977

  3. 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

  4. 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