Hi, I am Yovani Marrero Ponce, My LiveDNA is 53.6366
 
   
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Dr. Yovani Marrero Ponce
 
Highest Degree: Ph.D. in Chemical Sciences from Havana University, Cuba
 
Institute: Central University of Las Villas, Cuba
 
Area of Interest: Chemistry
  •   Drug Discovery and Molecular Design
  •   Chem-Bio-Informatics
  •   Computational Chemistry
  •   Molecular Modelling
 
URL: http://livedna.org/53.6366
 
My SELECTED Publications
1:    Marrero-Ponce, Y., M.T.H. Khan, G.M. Casanola-Martin, A. Ather, M.N. Sultankhodzhaev and F. Torrens, 2007. Atom-based 2D quadratic indices in drug discovery of novel tyrosinase inhibitors: Results of in silico studies supported by experimental results. QSAR Comb. Sci., 27: 469-487.
2:   Alvarado, Y.J., J. Baricelli, J. Caldera-Luzardo, N. Cubillan and G. Ferrer-Amado et al., 2011. Thermodynamics of solution, interaction with calf thymus DNA and anticancer activity of phenylhydrazone derivatives. J. Solut. Chem., 40: 26-39.
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3:   Alvarado, Y.J., M. Alvarez-Mon, J. Baricelli, J. Caldera-Luzardo and N. Cubillan et al., 2010. Solubility of thiophene-, furan- and pyrrole-2-carboxaldehyde phenylhydrazone derivatives in 2.82 mol.L−1 aqueous DMSO at 298.15 K, inhibition of lymphoproliferation and tubulin polymerization: A study based on the scaled particle theory. J. Solut. Chem., 39: 1099-1112.
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4:   Alvarado, Y.J., N. Cubillan, E. Chacin-Molero, G. Ferrer-Amado and P. Hernandez-Labarca et al., 2010. Experimental and theoretical determination of the limiting partial molar volume of indole in CCl4, tetrahydrofuran and acetonitrile at 293.15 K: A comparative study with benzimidazole and benzothiophene. J. Solut. Chem., 39: 277-290.
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5:   Alvarado, Y.J., N. Cubillan, M.G. Leal, P.H. Labarca, E. Michelena and Y. Marrero-Ponce, 2008. Experimental determination of the electronic polarizability of quinoline and isoquinoline in solution by three new strategies. J. Solut. Chem., 36: 1139-1155.
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6:   Alvares-Ginarte, Y.M., R. Crespo, L.A. Montero-Cabrera, J.A. Ruiz-Garcia and Y. Marrero-Ponce et al., 2005. A novel in-silico approach for qsar studies of anabolic and androgenic activities in the 17 β -hydroxy-5α-androstane steroid family. QSAR Comb. Sci., 24: 218-226.
7:   Alvarez-Ginarte, Y., R. Crespo-Otero, Y. Marrero-Ponce, A. Padron-Garcia and L.A. Montero-Cabrera, J.A. Ruiz-Garcia and F. Torrens, 2006. Quantitative structure-activity relationship and diversity analysis of the 4,5-dihydrotestosterone steroid family: Computational molecular models to test the anabolic/androgenic receptor. QSAR Comb. Sci., 25: 881-894.
8:   Alvarez-Ginarte, Y.M., L.A. Montero-Cabrera, J.M. Garcia de la Vega, P. Noheda-Marin, Y. Marrero-Ponce and J.A. Ruiz-Garcia, 2011. Anabolic and androgenic activities of 19-nor-testosterone steroids: QSAR study using quantum and physicochemical molecular descriptors. J. Steroid Biochem. Mol. Biol., 126: 35-45.
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9:   Alvarez-Ginarte, Y.M., R. Crespo-Otero, Y. Marrero-Ponce, P. Noheda-Marin and J.M. Garcia de la Vega et al., 2008. Chemometric and chemoinformatic analyses of anabolic and androgenic activities of testosterone and dihydrotestosterone analogues. Bioorg. Med. Chem., 16: 6448-6459.
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10:   Alvarez-Ginarte, Y.M., Y. Marrero-Ponce, J.A. Ruiz-Garcia, L.A. Montero-Cabrera and J.M. Garcia-de la Vega et al., 2008. Applying pattern recognition methods plus quantum and physico-chemical molecular descriptors to analyze the anabolic activity of structurally diverse steroids. J. Comput. Chem., 29: 317-333.
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11:   Alvarez-Ginarte,Y.M., L.A. Montero-Cabrera, J.M.G. de la Vega, A. Bencomo-Martinez and P. Pupo et al., 2013. Integration of ligand and structure-based virtual screening for identification of leading anabolic steroids. J. Steroid Biochem. Mol. Biol., 138: 348-358.
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12:   Barigye, S.J., Y. Marrero-Ponce, O.M. Santiago, Y.M. Lopez and F. Torrens, 2013. Shannon's, mutual, conditional and joint entropy information indices: Generalization of global indices defined from local vertex invariants. Curr. Comp. Aided Drug Des., 9: 164-183.
PubMed  |  Direct Link  |  
13:   Barigye, S.J., Y. Marrero-Ponce, V. Alfonso-Reguera and F. Perez-Gimenez, 2013. Extended GT-STAF information indices based on Markov approximation models. Chem. Phys. Lett., 570: 147-152.
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14:   Barigye, S.J., Y. Marrero-Ponce, Y. Martinez-Lopez, F. Torrens, A.L. Artiles-Martinez, R.W. Pino-Urias and O. Martinez-Santiago, 2013. Relations frequency hypermatrices in mutual, conditional and joint entropy-based information indices. J. Comput. Chem., 34: 259-274.
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15:   Barigye, S.J., Y. Marrero-Ponce, Y.M. Lopez, O. Martinez Santiago, F. Torrens, R. Garcia-Domenech and J. Galvez, 2013. Event-based criteria in GT-STAF information indices: Theory, exploratory diversity analysis and QSPR applications. SAR QSAR Environ. Res., 24: 3-34.
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16:   Borroto, O.M.R., Y.H. Diaz, J.M.G. de la Vega, R.C. Grau and Y.M. Ponce, 2012. Comparison of novel proximity models in Chemoinformatics. Afinidad, 560: 271-277.
17:   Brito-Sanchez, Y., J.A. Castillo-Garit, H. Le-Thi-Thu, Y. Gonzalez-Madariaga, F. Torrens, Y. Marrero-Ponce and J.E. Rodriguez-Borges, 2013. Comparative study to predict toxic modes of action of phenols from molecular structures. SAR QSAR Environ. Res., 24: 235-251.
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18:   Casanola-Martin, G.M. M.T.H. Khan, Y. Marrero-Ponce, A. Ather, S. Sultan, F. Torrens and R. Rotondo, 2007. TOMOCOMD-CARDD descriptors-based virtual screening of tyrosinase inhibitors: Evaluation of different classification model combinations using bond-based linear indices. Bioorg. Med. Chem., 15: 1483-1503.
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19:   Casanola-Martin, G.M., H. Le-Thi-Thu, Y. Marrero-Ponce, F. Torrens, A. Rescigno, C. Abad and M.T. Hassan Khan, 2012. QSAR-based CMs and TOMOCOMD-CARD Approach for the Discovery of New Tyrosinase Inhibitor Chemicals. In: Recent Trends on QSAR in the Pharmaeutical Perceptions, Hassan Khan, M.T. (Ed.). Chapter 10, Bentham, London, UK., pp: 296-337.
20:   Casanola-Martin, G.M., M.T. Hassan Khan, H. Le-Thi-Thu and Y. Marrero-Ponce et al., 2012. Retrained classification of tyrosinase inhibitors and ''In silico'' potency estimation by using atom-type linear indices: A powerful tool for speed up the discovery of leads. Int. J. Chemoinform. Chem. Engin., 2: 142-144.
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21:   Casanola-Martin, G.M., M.T.H. Khan, Y. Marrero-Ponce, A. Ather, M.N. Sultankhodzhaev and F. Torrens, 2006. New tyrosinase inhibitors selected by atomic linear indices-based classification models. Bioorg. Med. Chem. Letter., 16: 324-330.
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22:   Casanola-Martin, G.M., Y. Marrero-Ponce, M.T. Khan, S.B. Khan and F. Torrens et al., 2010. Bond-based 2D quadratic fingerprints in QSAR studies: Virtual and in vitro tyrosinase inhibitory activity elucidation. Chem. Biol. Drug Des., 76: 538-545.
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23:   Casanola-Martin, G.M., Y. Marrero-Ponce, M.T.H. Khan, A. Ather, T.M. Khan, M.K. Khan, F. Torrens and R. Rotondo, 2007. Dragon method for finding novel tyrosinase inhibitors: Biosilico identification and experimental in vitro assays. Eur. J. Med. Chem., 42: 1370-1381.
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24:   Casanola-Martin, G.M., Y. Marrero-Ponce, M.T.S. Khan, F. Torrens, F. Perez-Gimenez and A. Rescigno, 2008. Atom- and bond-based 2D TOMOCOMD-CARDD approach and ligand-based virtual screening for the drug discovery of new tyrosinase inhibitors. J. Biomol. Screen., 13: 1014-1024.
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25:   Castillo-Garit, J.A., C. Abad, J.E. Rodriguez-Borges, Y. Marrero-Ponce and F. Torrens, 2012. A review of QSAR studies to discover new drug-like compounds actives against leishmaniasis and trypanosomiasis. Curr. Top. Med. Chem., 12: 852-865.
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26:   Castillo-Garit, J.A., M. Celeste Vega, M. Rolon, Y. Marrero-Ponce and A. Gomez-Barrio et al., 2011. Ligand-based discovery of novel trypanosomicidal drug-like compounds: In silico identification and experimental support. Eur. J. Med. Chem., 46: 3324-3330.
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27:   Castillo-Garit, J.A., M.C. Vega, M. Rolond, Y. Marrero-Ponce and V. Kouznetsovf et al., 2010. Computational discovery of novel trypanosomicidal drug-like chemicals by using bond-based non-stochastic and stochastic quadratic maps and linear discriminant analysis. Eur. J. Pharm. Sci., 39: 30-36.
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28:   Castillo-Garit, J.A., O. Martinez-Santiago, Y. Marrero-Ponce, G.M. Casanola-Martin and F. Torrens, 2008. Atom-based non-stochastic and stochastic bilinear indices: Application to QSPR/QSAR studies of organic compounds. Chem. Phys. Lett., 464: 107-112.
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29:   Castillo-Garit, J.A., O.D. Toro-Cortes, V.V. Kouznetsov, C.O. Puentes and A.R.R. Bohorquez et al., 2012. Identification in silico and in vitro of novel trypanosomicidal drug-like compounds. Chem. Biol. Drug Des., 80: 38-45.
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30:   Castillo-Garit, J.A., R. Garcia-Domenech, Y. Marrero-Ponce, F. Torrens and C. Abad, 2011. Atom-based 3D-chiral quadratic indices. Part 3: Prediction of the binding affinity of the stereoisomers of fenoterol to the α-2 adrenergic receptor. Afinidad, 555: 333-340.
31:   Castillo-Garit, J.A., Y. Marrero-Ponce and F. Torrens, 2006. Atom-based 3D-chiral quadratic indices. Part 2: prediction of the corticosteroid-binding globulinbinding affinity of the 31 benchmark steroids data set. Bioorg. Med. Chem., 14: 2398-2408.
32:   Castillo-Garit, J.A., Y. Marrero-Ponce, F. Torrens and R. Garcia-Domenech, 2008. Estimation of ADME properties in drug discovery: Predicting caco-2 cell permeability using atom-based stochastic and non-stochastic linear indices. J. Pharm. Sci., 97: 1946-1976.
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33:   Castillo-Garit, J.A., Y. Marrero-Ponce, F. Torrens and R. Rotondo, 2007. Atom-based stochastic and non-stochastic 3d-chiral bilinear indices and their applications to central chirality codification. J. Mol. Graph. Model., 26: 32-47.
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34:   Castillo-Garit, J.A., Y. Marrero-Ponce, F. Torrens, R. Garcia-Domenech and J.E. Rodriguez-Borges, 2009. Applications of bond-based 3D-chiral quadratic indices in QSAR studies related to central chirality codification. QSAR Comb. Sci., 28: 1465-1477.
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35:   Castillo-Garit, J.A., Y. Marrero-Ponce, F. Torrens, R. Garcia-Domenech and V. Romero-Zaldivar, 2008. Bond-based 3D-chiral linear indices: Theory and QSAR applications to central chirality codification. J. Comput. Chem., 29: 2500-2512.
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36:   Castillo-Garit, J.A., Y. Marrero-Ponce, J. Escobar, F. Torrens and R. Rotondo, 2008. A novel approach to predict aquatic toxicity from molecular structure. Chemosphere, 73: 415-427.
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37:   Celeste-Vega, M., A. Montero-Torres, Y. Marrero-Ponce, M. Rolon and A. Gomez-Barrio et al., 2005. New ligand-based approach for the discovery of antitrypanosomal compounds. Bioorg. Med. Chem. Lett., 16: 1898-1904.
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38:   Diaz, G.H., Y. Marrero-Ponce, I. Hernandez, I. Bastida and E. Tenorio et al., 2003. 3D-MEDNEs: An alternative ''In Silico'' technique for chemical research in toxicology. 1. prediction of chemically induced agranulocytosis. Chem. Res. Toxicol., 16: 1318-1327.
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39:   Garit, J.A.C., R.G. Domenech, Y. Marrero-Ponce, F.T. Zaragoza and C. Abad, 2012. Prediction of the binding affinity between fenoterol derivatives and the β2-adrenergic receptor using atom-based 3D-chiral linear indices. Nereis, 4: 9-18.
40:   Ibarra-Velarde, F., Y. Vera-Montenegro, A. Huesca-Guillen, G. Canto-Alarcon, Y. Alcala-Canto and Y. Marrero-Ponce, 2008. In silico fasciolicide activity of three experimental compounds in sheep. Ann. N.Y. Acad. Sci., 1149: 183-185.
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41:   Le-Thi-Thu, H., G.C. Cardoso, G.M. Casanola-Martin, Y. Marrero-Ponce and A. Puris et al., 2010. QSAR models for tyrosinase inhibitory activity description applying modern statistical classification techniques: A comparative study. Chemom. Intell. Lab. Syst., 104: 249-259.
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42:   Le-Thi-Thu, H., G.M. Casanola-Martin, Y. Marrero-Ponce, A. Rescigno and L. Saso et al., 2011. Novel coumarin-based tyrosinase inhibitors discovered by OECD principles-validated QSAR approach from an enlarged, balanced database. Mol. Divers., 15: 507-520.
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43:   Le-Thi-Thu, H., Y. Marrero-Ponce, G.M. Casanola-Martin, G. Casas Cardoso and M.C. Chavez et al., 2011. A comparative study of nonlinear machine learning for the In silico depiction of tyrosinase inhibitory activity from molecular structure. Mol. Inf., 30: 527-537.
44:   Marrero-Ponce, Y. M.A. Cabrera, V. Romero-Zaldivar, M. Bermejo, D. Siverio and F. Torrens, 2005. Prediction of intestinal epithelial transport of drug in (Caco-2) cell culture from molecular structure using 'in silico' approaches during early drug discovery. Int. Electron. J. Mol. Des., 4: 124-150.
45:   Marrero-Ponce, Y., 2003. Total and local quadratic indices of the molecular pseudograph's atom adjacency matrix: applications to the prediction of physical properties of organic compounds. Molecules, 8: 687-726.
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46:   Marrero-Ponce, Y., 2004. Linear indices of the "molecular pseudograph's atom adjacency matrix": definition, significance-interpretation, and application to QSAR analysis of flavone derivatives as HIV-1 integrase inhibitors. J. Chem. Inf. Comput. Sci., 44: 2010-2026.
PubMed  |  
47:   Marrero-Ponce, Y., 2004. Total and local (atom and atom type) molecular quadratic indices: Significance interpretation, comparison to other molecular descriptors, and QSPR/QSAR applications. Bioorg. Med. Chem., 12: 6351-6369.
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48:   Marrero-Ponce, Y., A. Huesca-Guillen and F. Ibarra-Velarde, 2005. Quadratic indices of the 'molecular pseudograph's atom adjacency matrix' and their stochastic forms: a novel approach for virtual screening and in silico discovery of new lead paramphistomicide drugs-like compounds. J. Theor. Chem, Theochem, 717: 67-79.
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49:   Marrero-Ponce, Y., A. Huesca-Guillen, F. Torrens and F. Ibarra-Velarde, 2011. Novel ligand-based approach to screening of large databases for paramphistomicide lead generation. Nereis, 3: 9-15.
50:   Marrero-Ponce, Y., A. Meneses-Marcel, O.M. Rivera-Borroto, R. Garcia-Domenech and J.V. De Julian-Ortiz et al., 2008.. Bond-Based linear indices in QSAR studies: Chemoinformatics studies and computational discovery of novel trichomonacidal chemicals. J. Comput. Aided Mol. Des., 22: 523-540.
51:   Marrero-Ponce, Y., A. Meneses-Marcel, Y. Machado-Tugores, D. Montero Pereira and J.A. Escario et al., 2005. A computer-based approach to the rational discovery of new antitrichomonas drugs by atom-type linear indices. Curr. Drug Discov. Technol., 2: 245-265.
52:   Marrero-Ponce, Y., A. Meneses-Marcel, Y. Machado-Tugores, J.A. Escario and A. Gomez-Barrio et al., 2006. Predicting antitrichomonal activity: A computational screening using atom-based bilinear indices and experimental proofs. Bioorg. Med. Chem., 14: 6502-6524.
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53:   Marrero-Ponce, Y., A. Montero-Torres, C. Romero-Zaldivar, I. Iyarreta-Veitia, M.M. Perez and G.R. Sanchez, 2005. Non-stochastic and stochastic linear indices of the 'molecular pseudograph's atom adjacency matrix': application to 'in silico' studies for the rational discovery of new antimalarial compounds. Bioorg. Med. Chem., 13: 1293-1304.
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54:   Marrero-Ponce, Y., D. Nodarse, H. Gonzalez-Diaz, R. Ramos-Armas, V. Romero-Zaldivar, F. Torrens and E. Castro, 2004. Nucleic acid quadratic indices of the ''macromolecular graph's nucleotides adjacency matrix''. Int. J. Mol. Sci., 5: 276-293.
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55:   Marrero-Ponce, Y., D. Siverio-Mota, M. Galvez-Llompart, M.C. Recio and R.M. Giner et al., 2011. Discovery of novel anti-inflammatory drug-like compounds by aligning in silico and in vivo screening: The nitroindazolinone chemotype. Eur. J. Med. Chem., 46: 5736-5753.
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56:   Marrero-Ponce, Y., E.R. Martinez, G.M. Casanola-Martin, F. Perez-Gimenez, Y. Echeveria-Dias and J.E. Rodriguez-Borges, 2011. Bond-extended stochastic and nonstochastic bilinear indices. I. QSPR/QSAR applications to the description of properties/activities of small-medium size organic compounds. Int. J. Quant. Chem., 111: 8-34.
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57:   Marrero-Ponce, Y., F. Torrens, R. Garcia-Domenech, S. Ortega-Broche and V. Romero-Zaldivar, 2008. Novel 2D TOMOCOMD-CARDD molecular descriptors: Atom-based stochastic and non-stochastic bilinear indices and their QSPR applications. J. Math. Chem., 44: 650-673.
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58:   Marrero-Ponce, Y., F. Torrens, Y.J. Alvarado and R. Rotondo, 2006. Bond-based global and local (bond, group and bond-type) quadratic indices and their applications to computer-aided molecular design. 1. qspr studies of diverse sets of organic chemicals. J. Comput. Aided Mol. Des., 20: 685-701.
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59:   Marrero-Ponce, Y., G.M. Casanola-Martin, M.T.H. Khan, F. Torrens, A. Rescigno and C. Abad, 2010. Ligand-based computer-aided discovery of tyrosinase inhibitors. Applications of the TOMOCOMD-CARDD method to the elucidation of new compounds. Curr. Pharm. Des., 16: 2601-2624.
60:   Marrero-Ponce, Y., H. Gonzalez-Diaz, V. Romero-Zaldivar, F. Torrens and E.A. Castro, 2004. 3D-chiral quadratic indices of the 'molecular pseudograph's atom adjacency matrix' and their application to central chirality codification: classification of ACE inhibitors and prediction of sigma-receptor antagonist activities. Bioorg. Med. Chem., 12: 5331-5342.
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61:   Marrero-Ponce, Y., J.A. Castillo-Garit and D. Nodarse, 2005. Linear indices of the 'macromolecular graph's nucleotides adjacency matrix' as a promising approach for bioinformatics studies. Part 1: Prediction of paromomycin's affinity constant with HIV-1 Ψ-RNA packaging region. Bioorg. Med. Chem., 13: 3397-3404.
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62:   Marrero-Ponce, Y., J.A. Castillo-Garit, 2005. 3D-chiral atom, atom-type, and total non-stochastic and stochastic molecular linear indices and their applications to central chirality codification. J. Comput. Aided.Mol. Des., 19: 369-383.
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63:   Marrero-Ponce, Y., J.A. Castillo-Garit, E. Olazabal, H.S. Serrano and A. Morales et al., 2004. TOMOCOMD-CARDD a novel approach for computer-aided 'rational' drug design: I. Theoretical and experimental assessment of a promising method for computational screening and in silico design of new anthelmintic compounds. J. Comput. Aided Mol. Des., 18: 615-634.
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64:   Marrero-Ponce, Y., J.A. Castillo-Garit, E. Olazabal, H.S. Serrano and A. Morales et al., 2005. Atom, atom-type and total molecular linear indices as a promising approach for bioorganic and medicinal chemistry: Theoretical and experimental assessment of a novel method for virtual screening and rational design of new lead anthelmintic. Bioorg. Med. Chem., 13: 1005-1020.
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65:   Marrero-Ponce, Y., J.A. Castillo-Garit, E.A. Castro, F. Torrens and R. Rotondo, 2008. 3D-chiral (2.5) atom-based TOMOCOMD-CARDD descriptors: Theory and QSAR applications to central chirality codification. J. Math. Chem., 44: 755-786.
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66:   Marrero-Ponce, Y., J.A. Castillo-Garit, F. Torrens, V. Romero-Zaldivar and E. Castro, 2004. Atom, atom-type, and total linear indices of the "molecular pseudograph's atom adjacency matrix": application to QSPR/QSAR studies of organic compounds. Molecules, 9: 1100-1123.
PubMed  |  
67:   Marrero-Ponce, Y., M. Iyarreta, A. Montero, C. Romero and C.A. Brandt et al., 2005. Ligand-based virtual screening and in silico design of new antimalarial compounds using nonstochastic and stochastic total and atom-type quadratic maps. J. Chem. Inf. Comput. Sci., 45: 1082-1100.
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68:   Marrero-Ponce, Y., M.A. Cabrera, V. Romero, E. Ofori and L.A. Montero, 2003. Total and local quadratic indices of the molecular pseudograph's atom adjacency matrix: Application to prediction of Caco-2 permeability of drugs. Int. J. Mol. Sci., 4: 512-536.
69:   Marrero-Ponce, Y., M.T.H. Khan, G.M. Casanola-Martin, A. Ather, M.N. Sultankhodzhaev, F. Torrens and R. Rotondo, 2007. Prediction of tyrosinase inhibition activity using atom-based bilinear indices. Chem. Med. Chem., 2: 449-478.
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70:   Marrero-Ponce, Y., M.T.H. Khan, G.M. Casanola-Martin, A. Ather, M.T. Khan, M.K. Khan, F.Torrens and R. Rotondo, 2007. Bond-based 2D TOMOCOMD-CARDD approach for drug discovery: aiding decision-making in 'in silico' selection of new lead tyrosinase inhibitors. J. Comput. Aided Mol. Des., 21: 167-188.
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71:   Marrero-Ponce, Y., O. Martinez Santiago, Y. Martinez Lopez, S.J. Barigye and F. Torrens, 2012. Derivatives in discrete mathematics: A novel graph-theoretical invariant for generating new 2/3D molecular descriptors. I. Theory and QSPR application. J. Comput. Aided Mol. Des., 26: 1229-1246.
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72:   Marrero-Ponce, Y., R. Medina, E.A. Castro, R. de Armas, H. Gonzalez, V. Romero and F. Torrens, 2004. Protein quadratic indices of the ''macromolecular pseudograph's α-carbon atom adjacency matrix''. 1. prediction of arc repressor alanine-mutant's stability. Molecules, 9: 1124-1147.
73:   Marrero-Ponce, Y., R. Medina-Marrero, J.A. Castillo-Garit, V. Romero-Zaldivar, F. Torrens and E.A. Castro, 2005. Atom, atom-type, and total nonstochastic and stochastic quadratic fingerprints: a promising approach for modeling of antibacterial activity. Bioorg. Med. Chem., 13: 2881-2899.
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74:   Marrero-Ponce, Y., R. Medina-Marrero, J.A. Castillo-Garit, V. Romero-Zaldivar, F. Torrens and E.A. Castro, 2005. Protein linear indices of the ''macromolecular pseudograph's α-carbon atom adjacency matrix'' in bioinformatics. part 1. prediction of protein stability effects of a complete set of alanine substitutions in arc repressor. Bioorg. Med. Chem., 13: 3003-3015.
75:   Marrero-Ponce, Y., R. Medina-Marrero, Y. Martinez, F. Torrens, V. Romero-Zaldivar, E.A. Castro, 2006. Non-stochastic and stochastic linear indices of the molecular pseudograph's atom-adjacency matrix: a novel approach for computational in silico screening and "rational" selection of new lead antibacterial agents. J. Mol. Mod., 12: 255-271.
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76:   Marrero-Ponce, Y., R.E. Martinez, G.M. Casanola-Martin, J.A. Castillo-Garit and Y. Echeveria-Diaz et al., 2010. Bond-based linear indices of the non-stochastic and stochastic edge-adjacency matrix. 1. Theory and modeling of ChemPhys properties of organic molecules. Mol. Div., 14: 731-753.
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77:   Marrero-Ponce, Y., S.E. Ortega-Broche, Y. Echeveria-Diaz, Y.J. Alvardo and N. Cubillan et al., 2008. Nucleotide's bilinear indices: Novel bio-macromolecular descriptors for bioinformatics studies of nucleic acids. I. Prediction of paromomycin's affinity constant with HIV-1 Ψ-RNA packaging region. J. Theor. Biol., 259: 229-241.
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78:   Martinez Albelo, E.R., Y. Marrero Ponce, S.J. Barigye, Y. Echeverria-Diaz and F. Perez-Gimenez, 2013. QSPR/QSAR studies of 2-furylethylenes using bond-level quadratic indices and comparison with other computational approaches. J. Mex. Chem. Soc., 57: 61-68.
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79:   Meneses-Marcel, A., O.M. Rivera-Borroto, Y. Marrero-Ponce, A. Montero and Y. Machado-Tugores et al., 2008. New antitrichomonal drug-like chemicals selected by bond (edge)-based TOMOCOMD-CARDD descriptors. J. Biomol. Screen., 13: 785-794.
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80:   Meneses-Marcel, A., Y. Marrero-Ponce, Y. Machado-Tugores, A. Montero-Torres and D. Montero et al., 2005. A linear discrimination analysis based virtual screening of trichomonacidal lead-like compounds: Outcomes of in silico studies supported by experimental results. Bioorg. Med. Chem Lett., 17: 3838-3843.
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81:   Montero-Torres, A., A. Celeste Vega, Y. Marrero-Ponce, M. Rolon and A. Gomez-Barrio et al., 2005. A novel non-stochastic quadratic fingerprints-based approach for the 'in silico' discovery of new antitrypanosomal compounds. Bioorg. Med. Chem., 13: 6264-6275.
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82:   Montero-Torres, A., R.N. Garcia, Y. Marrero-Ponce, Y. Machado-Tugores and J.J. Nogal et al., 2006. Non-stochastic quadratic fingerprints and LDA-based QSAR models in hit and lead generation through virtual screening: theoretical and experimental assessment of a promising method for the discovery of new antimalarial compounds. Eur. J. Med. Chem., 41: 483-493.
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83:   Ortega-Broche, S.E., Y. Marrero-Ponce, Y. Echeveria-Diaz, F. Torrens and F. Perez-Gimenez, 2010. TOMOCOMD-CAMPS and protein bilinear indices-novel bio-macromolecular descriptors for protein research: I. Predicting protein stability effects of a complete set of alanine substitutions in the Arc repressor. FEBS J., 277: 3118-3146.
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84:   Ponce, Y.M., M.A.C. Perez, V.R. Zaldivar, H.G. Diaz and F. Torrens, 2004. A new topological descriptors based model for predicting intestinal epithelial transport of drugs in Caco-2 cell culture. J. Pharm. Pharmaceut. Sci., 7: 186-199.
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85:   Rescigno, A., G.M. Casanola-Martin, E. Sanjust, P. Zucca and Y. Marrero-Ponce, 2011. Vanilloid derivatives as tyrosinase inhibitors driven by virtual screening-based QSAR models. Drug Test Anal., 3: 176-181.
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86:   Rivera Borroto, O.M., Y. Hernandez Diaz, J.M. Garcia de la Vega, R.G. Grau Abalo and Y. Marrero-Ponce, 2011. Novel similarity measures for the effective and efficient retrieval of pharmacological datasets. Afinidad, 551: 50-56.
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87:   Rivera, N., M. Rojas, A. Zepeda, F. Malagon and V.J. Aran et al., 2013. In vivo genotoxicity and cytotoxicity assessment of a novel quinoxalinone with trichomonacide activity. J. Applied Toxicol., 33: 1493-1499.
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88:   Rivera, N., Y. Marrero Ponce, V.J. Aran, C. Martinez and F. Malagon, 2013. Biological assay of a novel quinoxalinone with antimalarial efficacy on Plasmodium yoelii yoelii. Parasitol. Res., 112: 1523-1527.
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89:   Rivera-Borroto, M.O., M. Rabassa-Gutierrez, R. Grau-Abalo, Y. Marrero-Ponce and J.M. Garcia-de la Vega, 2012. Dunn's index for cluster tendency assessment of pharmacological data sets. Can. J. Phys. Pharm., 90: 425-433.
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90:   Rivera-Borroto, O., Y. Marrero-Ponce, A. Meneses-Marcel, J.A. Escario and Gomez-Barrio et al., 2008. Discovery of novel trichomonacidals via virtual screening using LDA-driven QSAR models and bond-based bilinear indices as molecular descriptors. QSAR Comb. Sci., 28: 9-26.
91:   Rivera-Borroto, O.M., Y. Marrero-Ponce, J.M. Garcia-de la Vega and R.C. do Grau-Abalo, 2011. Comparison of combinatorial clustering methods on pharmacological data sets represented by machine learning-selected real molecular descriptors. J. Chem. Inform. Comput. Sci., 51: 3036-3049.
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92:   Roldos, V., H. Nakayama, M. Rolon, A. Montero-Torres and F. Trucco et al., 2008. Activity of a Hydroxybibenzyl bryophyte constituent against Leishmania spp. and Trypanosoma cruzi: In silico, in vitro and in vivo activity studies. Eur. J. Med. Chem., 43: 1797-1807.
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93:   Ruiz-Blanco, Y., Y. Garcia, C.M. Sotomayor-Torres and Y. Marrero-Ponce, 2010. New Set of 2D/3D thermodynamic indices for proteins. A formalism based on Molten Globule theory. Phys. Procedia, 8: 63-72.
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94:   Ruiz-Blanco, Y.B., Y. Marrero-Ponce, W. Paz, Y. Garcia and J. Salgado, 2013. Global stability of protein folding from an empirical free energy function. J. Theor. Biol., 321: 44-53.
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95:   Tugores, M.Y., A.M. Marcel, M.Y. Ponce, V.J. Aran and J.A.E. Garcia-Trevijano et al., 2012. Discovery of new antimalarials from commercial drugs by in silico and in vitro screening. Real Acad. Nac. Farm., 78: 401-416.
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96:   Vega, M.C., M. Rolon, A. Montero-Torres, C. Fonseca-Berzal and J.A. Escario et al., 2012. Synthesis, biological evaluation and chemometric analysis of indazole derivatives. 1,2-Disubstituted 5-nitroindazolinones, new prototypes of antichagasic drug. Eur. J. Med. Chem., 58: 214-227.
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