Publicaciones (14) Publicaciones de José Liñares Blanco

2024

  1. VIBES: A consensus subtyping of the vaginal microbiota reveals novel classification criteria

    Computational and Structural Biotechnology Journal, Vol. 23, pp. 148-156

2022

  1. Machine Learning Based Microbiome Signature to Predict Inflammatory Bowel Disease Subtypes

    Frontiers in Microbiology, Vol. 13

2021

  1. A review on machine learning approaches and trends in drug discovery

    Computational and Structural Biotechnology Journal, Vol. 19, pp. 4538-4558

  2. Bioinformatic tools for research in CRC

    Foundations of Colorectal Cancer (Elsevier), pp. 231-247

  3. La Inteligencia Artificial como herramienta para la gestión y explotación de datos, informaciones y conocimientos biomédicos en entornos “Big Data” en la nube

    I+S: Revista de la Sociedad Española de Informática y Salud, Núm. 143, pp. 30-39

  4. Machine Learning Algorithms Reveals Country-Specific Metagenomic Taxa from American Gut Project Data

    Studies in health technology and informatics, Vol. 281, pp. 382-386

  5. Machine Learning analysis of the human infant gut microbiome identifies influential species in type 1 diabetes

    Expert Systems with Applications, Vol. 185

  6. Machine learning analysis of TCGA cancer data

    PeerJ Computer Science, Vol. 7, pp. 1-47

2020

  1. Molecular docking and machine learning analysis of Abemaciclib in colon cancer

    BMC Molecular and Cell Biology, Vol. 21, Núm. 1

2019

  1. Differential Gene Expression Analysis of RNA-seq Data Using Machine Learning for Cancer Research

    Learning and Analytics in Intelligent Systems (Springer Nature), pp. 27-65

  2. Gene Signatures Research Involved in Cancer Using Machine Learning

    XoveTIC 2019: The 2nd XoveTIC Conference (XoveTIC 2019), A Coruña, Spain, 5–6 September

  3. Prediction of Peptide Vascularization Inhibitory Activity in Tumor Tissue as a Possible Target for Cancer Treatment

    XoveTIC 2019: The 2nd XoveTIC Conference (XoveTIC 2019), A Coruña, Spain, 5–6 September

2018

  1. Integrative multi-omics data-driven approach for metastasis prediction in cancer

    ACM International Conference Proceeding Series

  2. Prediction of high anti-angiogenic activity peptides in silico using a generalized linear model and feature selection

    Scientific Reports, Vol. 8, Núm. 1