Drug R&D
GI-1606
Universidad Central de Las Villas
Santa Clara, CubaPublications in collaboration with researchers from Universidad Central de Las Villas (37)
2015
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Métodos grafo-numéricos de relevancia para la bioinformática. Aplicaciones en la biotecnología vegetal y en el descubrimiento de fármacos
Anales de la Academia de Ciencias de Cuba, Vol. 5, Núm. 3
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
2009
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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
2008
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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
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
2006
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A QSAR model for in silico screening of MAO-A inhibitors. Prediction, synthesis, and biological assay of novel coumarins
Journal of Medicinal Chemistry, Vol. 49, Núm. 3, pp. 1149-1156
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Novel 2D maps and coupling numbers for protein sequences. The first QSAR study of polygalacturonases; isolation and prediction of a novel sequence from Psidium guajava L.
FEBS Letters, Vol. 580, Núm. 3, pp. 723-730
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QSAR study for mycobacterial promoters with low sequence homology
Bioorganic and Medicinal Chemistry Letters, Vol. 16, Núm. 3, pp. 547-553
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Simple stochastic fingerprints towards mathematical modeling in biology and medicine 2. Unifying Markov model for drugs side effects
Bulletin of Mathematical Biology, Vol. 68, Núm. 7, pp. 1527-1554
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Stochastic entropy QSAR for the in silico discovery of anticancer compounds: Prediction, synthesis, and in vitro assay of new purine carbanucleosides
Bioorganic and Medicinal Chemistry, Vol. 14, Núm. 4, pp. 1095-1107
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Unify QSAR approach to antimicrobials. Part 1: Predicting antifungal activity against different species
Bioorganic and Medicinal Chemistry, Vol. 14, Núm. 17, pp. 5973-5980
2005
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2D RNA-QSAR: Assigning ACC oxidase family membership with stochastic molecular descriptors; isolation and prediction of a sequence from Psidium guajava L
Bioorganic and Medicinal Chemistry Letters, Vol. 15, Núm. 11, pp. 2932-2937
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3D QSAR Markov model for drug-induced eosinophilia - Theoretical prediction and preliminary experimental assay of the antimicrobial drug G1
Bioorganic and Medicinal Chemistry, Vol. 13, Núm. 5, pp. 1523-1530
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Biopolymer stochastic moments. I. Modeling human rhinovirus cellular recognition with protein surface electrostatic moments
Biopolymers, Vol. 77, Núm. 5, pp. 296-303
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Markovian chemicals "in silico" design (MARCH-INSIDE), a promising approach for computer-aided molecular design III: 2.5D indices for the discovery of antibacterials
Journal of Molecular Modeling, Vol. 11, Núm. 2, pp. 116-123
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Predicting multiple drugs side effects with a general drug-target interaction thermodynamic Markov model
Bioorganic and Medicinal Chemistry, Vol. 13, Núm. 4, pp. 1119-1129
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Predicting stability of Arc repressor mutants with protein stochastic moments
Bioorganic and Medicinal Chemistry, Vol. 13, Núm. 2, pp. 323-331