Publications in collaboration with researchers from Universidad Central de Las Villas (10)

2016

  1. Exploring different strategies for imbalanced ADME data problem: case study on Caco-2 permeability modeling

    Molecular Diversity, Vol. 20, Núm. 1, pp. 93-109

  2. Importance and applications of cell-and tissue-based in vitro models for drug permeability screening in early stages of drug development

    Concepts and Models for Drug Permeability Studies: Cell and Tissue based In Vitro Culture Models (Elsevier Inc.), pp. 3-29

2015

  1. Harmonization of QSAR Best Practices and Molecular Docking Provides an Efficient Virtual Screening Tool for Discovering New G-Quadruplex Ligands

    Journal of Chemical Information and Modeling, Vol. 55, Núm. 10, pp. 2094-2110

  2. Importance and applications of cell- and tissue-based in vitro models for drug permeability screening in early stages of drug development

    Concepts and Models for Drug Permeability Studies: Cell and Tissue based in Vitro Culture Models (Elsevier), pp. 3-29

  3. Nueva estrategia computacional - experimental para la clasificación biofarmacéutica de fármacos y su implementación para la obtención de medicamentos genéricos y productos farmacéuticos de avanzada.

    Anales de la Academia de Ciencias de Cuba, Vol. 5, Núm. 3

2013

  1. Provisional classification and in silico study of biopharmaceutical system based on Caco-2 cell permeability and dose number

    Molecular Pharmaceutics, Vol. 10, Núm. 6, pp. 2445-2461

  2. The use of rule-based and QSPR approaches in ADME profiling: A case study on caco-2 permeability

    Molecular Informatics, Vol. 32, Núm. 5-6, pp. 459-479

2012

  1. Computational tools in the discovery of new G-quadruplex ligands with potential anticancer activity

    Current Topics in Medicinal Chemistry, Vol. 12, Núm. 24, pp. 2843-2856

  2. QSPR in oral bioavailability: Specificity or integrality?

    Mini-Reviews in Medicinal Chemistry, Vol. 12, Núm. 6, pp. 534-550

2011

  1. In silico prediction of caco-2 cell permeability by a classification QSAR approach

    Molecular Informatics, Vol. 30, Núm. 4, pp. 376-385