Facultade de Farmacia
Facultad
Universidad Central de Las Villas
Santa Clara, CubaPublicacións en colaboración con investigadores/as de Universidad Central de Las Villas (55)
2019
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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
2014
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Model for high-throughput screening of drug immunotoxicity - Study of the anti-microbial G1 over peritoneal macrophages using flow cytometry
European Journal of Medicinal Chemistry, Vol. 72, pp. 206-220
2013
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Classifier ensemble based on feature selection and diversity measures for predicting the affinity of A2B adenosine receptor antagonists
Journal of Chemical Information and Modeling, Vol. 53, Núm. 12, pp. 3140-3155
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Combining QSAR classification models for predictive modeling of human monoamine oxidase inhibitors
European Journal of Medicinal Chemistry, Vol. 59, pp. 75-90
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Entropy model for multiplex drug-target interaction endpoints of drug immunotoxicity
Current Topics in Medicinal Chemistry, Vol. 13, Núm. 14, pp. 1636-1649
2012
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ANN multiplexing model of drugs effect on macrophages; Theoretical and flow cytometry study on the cytotoxicity of the anti-microbial drug G1 in spleen
Bioorganic and Medicinal Chemistry, Vol. 20, Núm. 20, pp. 6181-6194
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Immunotoxicity, flow cytometry, and chemoinformatics: Review, bibliometric analysis, and new QSAR model of drug effects over macrophages
Current Topics in Medicinal Chemistry, Vol. 12, Núm. 16, pp. 1815-1833
2010
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Design, synthesis, and evaluation of antineoplastic activity of novel carbocyclic nucleosides
Molecular Informatics, Vol. 29, Núm. 3, pp. 213-231
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QSAR for RNases and theoretic-experimental study of molecular diversity on peptide mass fingerprints of a new Leishmania infantum protein
Molecular Diversity, Vol. 14, Núm. 2, pp. 349-369
2009
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A TOPological Sub-structural Molecular Design (TOPS-MODE)-QSAR approach for modeling the antiproliferative activity against murine leukemia tumor cell line (L1210)
Bioorganic and Medicinal Chemistry, Vol. 17, Núm. 2, pp. 537-547
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Alignment-free prediction of mycobacterial DNA promoters based on pseudo-folding lattice network or star-graph topological indices
Journal of Theoretical Biology, Vol. 256, Núm. 3, pp. 458-466
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Alignment-free prediction of polygalacturonases with pseudofolding topological indices: Experimental isolation from coffea arabica and prediction of a new sequence
Journal of Proteome Research, Vol. 8, Núm. 4, pp. 2122-2128
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Theoretical prediction of antiproliferative activity against murine leukemia tumor cell line (L1210). 3D-morse descriptor and its application in computational chemistry)
QSAR and Combinatorial Science, Vol. 28, Núm. 1, pp. 98-110
2008
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HP-Lattice QSAR for dynein proteins: Experimental proteomics (2D-electrophoresis, mass spectrometry) and theoretic study of a Leishmania infantum sequence
Bioorganic and Medicinal Chemistry, Vol. 16, Núm. 16, pp. 7770-7776
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Quantitative structure-antibacterial activity relationship modeling using a combination of piecewise linear regression-discriminant analysis (I): Quantum chemical, topographic, and topological descriptors
International Journal of Quantum Chemistry
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Stochastic molecular descriptors for polymers. 4. Study of complex mixtures with topological indices of mass spectra spiral and star networks: The blood proteome case
Polymer, Vol. 49, Núm. 25, pp. 5575-5587
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Synthesis of new mannosyl, galactosyl and glucosyl theophylline nucleosides with potential activity as antagonists of adenosine receptors. DEMA-induced cyclization of glycosylideneiminouracils
Carbohydrate Research, Vol. 343, Núm. 5, pp. 855-864
2007
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ANN-QSAR model for selection of anticancer leads from structurally heterogeneous series of compounds
European Journal of Medicinal Chemistry, Vol. 42, Núm. 5, pp. 580-585
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Chemometrics for QSAR with low sequence homology: Mycobacterial promoter sequences recognition with 2D-RNA entropies
Chemometrics and Intelligent Laboratory Systems, Vol. 85, Núm. 1, pp. 20-26
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Probing the anticancer activity of nucleoside analogues: A QSAR model approach using an internally consistent training set
Journal of Medicinal Chemistry, Vol. 50, Núm. 7, pp. 1537-1545