1. D. K. Agrafiotis*, “Molecular orbital studies of dihydrogen transfers and other reactions”, Ph.D. Thesis, Department of Chemistry, Imperial College of Science & Technology, University of London, 1988.

  2. T. L. Graybill*, D. K. Agrafiotis, R. Bone, C. R. Illig, E. P. Jaeger, K. T. Locke, T. Lu, J. M. Salvino, R. M. Soll, J. C. Spurlino, N. Subasinghe, B. E. Tompczuk, and F. R. Salemme, “Enhancing the drug discovery process by integration of high-throughput chemistry and structure-based drug design”, in Molecular Diversity and Combinatorial Chemistry, Chaiken, I. M, and Janda, K. D., Eds., ACS, Washington D. C., 1996, 16-26.

  3. D. K. Agrafiotis*, “Diversity of chemical libraries”, in The Encyclopedia of Computational Chemistry; Schleyer, P.v.R.; Allinger, N. L.; Clark, T.; Gasteiger, J.; Kollman, P. A.; Schaefer III, H. F.; Schreiner, P. R., Eds., John Wiley and Sons, Chichester, 1998, Vol. 1, 742-761. [PDF]

  4. D. K. Agrafiotis*, J. P. Myslik, and F. R. Salemme, “Advances in diversity profiling and combinatorial series design”, in Annual Reports in Combinatorial Chemistry and Molecular Diversity, Pavia, M., and Moos, W., Eds., Kluwer, 1999, 2, 71-92.

  5. D. K. Agrafiotis*, V. S. Lobanov, D. N. Rassokhin, and S. Izrailev, “The measurement of molecular diversity”, in Virtual Screening of Bioactive Molecules, Böhm, H.-J., and Schneider, G., Eds., Wiley-VCH, Weinheim, 2000, 265-300.

  6. M. Farnum, R. DesJarlais, and D. K. Agrafiotis*, "Molecular diversity", in Chemoinformatics - From Data to Knowledge, Gasteiger, J., Ed., John Wiley and Sons, Chichester, 2003 (in press).

  7. A. C. Gibbs, and D. K. Agrafiotis*, "Chemical diversity: definition and quantification", in Exploiting Chemical Diversity for Drug Discovery, Bartlett, P., Entzeroth, M., Eds., The Royal Society of Chemistry, 2006, 139-160.
     


 

  1. D. K. Agrafiotis, and H. S. Rzepa*, "Dihydrogen transfer reactions. An SCF-MO study of the relative energies of the concerted and stepwise pathways.", J. Chem. Soc., Chem. Commun., 1987, 902

  2. D. K. Agrafiotis, and H. S. Rzepa*, "Evaluation of the Broyden-Fletcher-Goldfarb-Shanno (BFGS) variable metric method in geometry optimisation using semi-empirical SCF-MO procedures.", J. Chem. Research (S), 1988, 101.

  3. D. K. Agrafiotis, and H. S. Rzepa*, "A theoretical MNDO and AM1 SCF-MO study of dihydrogen elimination reactions.", J. Chem. Soc., Perkin Trans. II, 1989, 367.

  4. D. K. Agrafiotis, and H. S. Rzepa*, "A theoretical MNDO and AM1 SCF-MO study of dihydrogen transfer reactions", J. Chem. Soc., Perkin Trans. II, 1989, 475.

  5. D. K. Agrafiotis*, A. Streitwieser, and H. S. Rzepa, “MOECULE: GKS graphical display package”, QCPE Bull., 1989, 9, 127, Program 583.

  6. P. Wang, D. K. Agrafiotis, A. Streitwieser*, and P. v. R. Schleyer*, "Berry and turnstyle processes in the preudorotation of three phosphoranes."J. Chem. Soc., Chem. Commun., 1990, 201.

  7. D. K. Agrafiotis, B. L. Tansy and A. Streitwieser*, "PRODEN, a new electron density analysis program.", J. Comp. Chem., 1990, 11(9), 1101.

  8. D. K. Agrafiotis*, B. Tansy, and A. Streitwieser, “PRODEN: A new electron density analysis program”, QCPE Bull., 1991, 11, 13, Program 600.

  9. K. Spiegel, D. K. Agrafiotis, B. Carpathe, R. E. Davis, M. R. Dickerson, J. H. Fergus, T. W. Hepburn, J. S. Marks, M. van Dorf, D. M. Wieland, and J. C. Jaen*, “PD 90780, a non-peptide inhibitor of nerve growth factor’s binding to the P75 NGF receptor”, Biochem. Biophys. Res. Comm., 1995, 217(2), 488.

  10. D. K. Agrafiotis*, “Stochastic algorithms for maximizing molecular diversity”, 3-rd Electronic Computational Chemistry Conference, 1996.

  11. D. K. Agrafiotis*, “A new method for analyzing protein sequence relationships based on Sammon maps”, Protein Sci., 1997, 6(2), 287. [PDF]

  12. D. K. Agrafiotis*, “On the use of information theory for assessing molecular diversity”, J. Chem. Info. Comp. Sci., 1997, 37(3), 576. [PDF]

  13. D. K. Agrafiotis*, “Stochastic algorithms for maximizing molecular diversity”, J. Chem. Info. Comp. Sci., 1997, 37(5), 841. [PDF]

  14. D. K. Agrafiotis*, J. P. Myslik, and F. R. Salemme, “Advances in diversity profiling and combinatorial series design”, Mol. Diversity, 1999, 4, 1-22. [PDF]

  15. D. K. Agrafiotis*, and V. S. Lobanov, “An efficient implementation of distance-based diversity metrics based on k-d trees”, J. Chem. Info. Comp. Sci., 1999, 39(1), 51-58. [PDF]

  16. V. S. Lobanov*, and D. K. Agrafiotis, “Stochastic similarity selections from large combinatorial libraries”, J. Chem. Info. Comput. Sci., 2000, 40, 460-470. [PDF]

  17. D. K. Agrafiotis*, and V. S. Lobanov, “Ultrafast algorithm for designing focused combinatorial arrays”, J. Chem. Info. Comput. Sci., 2000, 40, 1030-1038. [PDF]

  18. D. B. Boyd, D. K. Agrafiotis, and E. J. Martin, "Introduction and forward to the special issue on combinatorial library design", J. Mol. Graphics Modell., 2000, 18, 317-319.

  19. D. N. Rassokhin, and D. K. Agrafiotis*, “Kolmogorov-Smirnov statistic and its applications in library design”, J. Mol. Graphics Modell., 2000, 18(4-5), 370-384. [PDF]

  20. D. K. Agrafiotis*, and V. S. Lobanov, “Nonlinear mapping networks”, J. Chem. Info. Comput. Sci., 2000, 40, 1356-1362. [PDF]

  21. D. K. Agrafiotis*, “A constant time algorithm for estimating the diversity of large chemical libraries”, J. Chem. Info. Comput. Sci., 2001, 41(1), 159-167 [PDF].

  22. S. Izrailev*, and D. K. Agrafiotis, “A new method for building regression tree models for QSAR based on artificial ant colony systems”, J. Chem. Info. Comput. Sci., 2001, 41(1), 176-180. [PDF]

  23. D. N. Rassokhin, V. S. Lobanov, and D. K. Agrafiotis*, “Nonlinear mapping of massive data sets by fuzzy clustering and neural networks”, J. Comput. Chem., 2001, 22(4), 373-386. [PDF]

  24. D. K. Agrafiotis*, D. N. Rassokhin, V. S. Lobanov, “Multidimensional scaling and visualization of large molecular similarity tables”, J. Comput. Chem., 2001, 22(5), 488-500. [PDF]

  25. D. K. Agrafiotis* and D. N. Rassokhin, "Design and prioritization of plates for high-throughput screening", J. Chem. Info. Comput. Sci., 2001, 41(3), 798-805. [PDF]

  26. D. K. Agrafiotis*, “Multiobjective optimization of combinatorial libraries”, IBM J. Res. Develop., 2001, 45(3/4), 545-566. ( Special Issue on Deep Computing in the Life Sciences). [PDF]

  27. V. S. Lobanov* and D. K. Agrafiotis, “Combinatorial networks”, J. Mol. Graphics Modell., 2001, 19(6), 571-578. [PDF]

  28. D. K. Agrafiotis and V. S. Lobanov*, "Multidimensional scaling of combinatorial libraries without explicit enumeration", J. Comput. Chem., 2001, 22(14), 1712-1722. [PDF]

  29. S. Izrailev*, and D. K. Agrafiotis, "Variable selection for QSAR by artificial ant colony systems", SAR and QSAR in Environ. Res., 2002, 13, 417-423. [PDF]

  30. D. K. Agrafiotis*, and D. N. Rassokhin, "A fractal approach for selecting an appropriate bin size for cell-based diversity estimation", J. Chem. Info. Comput. Sci., 2002, 42, 117-122. [PDF]

  31. V. S. Lobanov* and D. K. Agrafiotis, “Scalable methods for the construction and analysis of virtual combinatorial libraries”, Combin. Chem. High-Throughput Screen., 2002, 5, 167-178. [PDF]

  32. D. K. Agrafiotis*, and W. Cedeño, "Feature selection for structure-activity correlation using binary particle swarms", J. Med. Chem., 2002, 45, 1098-1107. [PDF]

  33. D. K. Agrafiotis*, V. S. Lobanov, and F. R. Salemme, "Combinatorial informatics in the post-genomics era, Nature Rev. Drug Discov., 2002, 1, 337-346. [PDF]

  34. D. K. Agrafiotis*, W. Cedeño, and V. S. Lobanov, "On the use of neural network ensembles in QSAR and QSPR", J. Chem. Info. Comput. Sci., 2002, 42, 903-911. [PDF]

  35. H. Xu*, and D. K. Agrafiotis, "Retrospect and prospect of virtual screening in drug lead discovery", Curr. Topics Med. Chem., 2002, 2, 1305-1320. [PDF]

  36. D. K. Agrafiotis*, “Multiobjective optimization of combinatorial libraries”, J. Comput. Aid. Mol. Des., 2002, 16, 335-356. [PDF]

  37. W. Cedeño, and D. K. Agrafiotis, "Combining particle swarms and k-nearest neighbors for the development of quantitative structure-activity relationships", Int. J. Comput. Res., 2002, 11, 443-452. [PDF]

  38. W. Cedeño* and D. K. Agrafiotis, "Application of niching particle swarms to QSAR and QSPR", Proceedings of the 14-th European Symposium on QSAR, Bournemouth, UK, September 8-13, 2002. [PDF]

  39. D. K. Agrafiotis,* and H. Xu, "A self-organizing principle for learning nonlinear manifolds", Proc. Natl. Acad. Sci. USA, 2002, 99, 15869-15872. [PDF]

  40. D. K. Agrafiotis*, "Stochastic proximity embedding", J. Comput. Chem., 2003, 24, 1215-1221. [PDF]

  41. D. K. Agrafiotis*, and H. Xu, "A geodesic framework for analyzing molecular similarities", J. Chem. Info. Comput. Sci., 2003, 43, 475-484. [PDF]

  42. W. Cedeño*, and D. K. Agrafiotis, "Using particle swarms for the development of QSAR models based on k-nearest neighbor and kernel regression", J. Comput. Aid. Mol. Des., 2003, 17, 255-263. [PDF]

  43. D. N. Rassokhin* and D. K. Agrafiotis, "A modified update rule for stochastic proximity embedding", J. Mol. Graphics Modell., 2003, 22, 133-140. [PDF]

  44. M. Farnum, H. Xu and D. K. Agrafiotis*, "Exploring the nonlinear geometry of sequence homology", Protein Sci., 2003, 12, 1604-1612. [PDF]

  45. H. Xu, S. Izrailev, and D. K. Agrafiotis*, "Conformational sampling by self-organization", J. Chem. Info. Comput. Sci., 2003, 43, 1186-1191. [PDF]

  46. H. Xu*, and D. K. Agrafiotis, "Nearest neighbor search in general metric spaces using a tree data structure with a simple heuristic", J. Chem. Info. Comput. Sci., 2003, 43, 1933-1941. [PDF]

  47. S. Izrailev*, and D. K. Agrafiotis, "A method for quantifying and visualizing the diversity of QSAR models", J. Mol. Grphics Modell., 2004, 22, 275-284. [PDF]

  48. M. Seierstad*, and D. K. Agrafiotis, "A QSAR model of hERG binding using a large, diverse and internally consistent training set", Chem. Biol. Drug. Des., 2006, 67(4), 284-296. [PDF]

  49. S. Izrailev, F. Zhu, and D. K. Agrafiotis*, "A distance geometry heuristic for expanding the range of geometries sampled during conformational search", J. Comput. Chem., 2006, 27(16), 1962-1969. [PDF]

  50. M. F. M. Engels*, A. Gibbs, E. P. Jaeger, D. Verbinnen, V. S. Lobanov, and D. K. Agrafiotis, "A clustering method for assessing the overlap between large chemical libraries and its application to a recent acquisition", J. Chem. Info. Model., 2006, 46, 2651-2660. [PDF]

  51. D. K. Agrafiotis*, A. Gibbs, F. Zhu, S. Izrailev, and E. Martin, "Conformational boosting", Aust. J. Chem. (special issue on Pacifichem 2005), 2006, 59, 874-878. [PDF]

  52. D. K. Agrafiotis*, D. Bandyopadhyay, and M. Farnum, "Radial clustergrams: visualizing the aggregate properties of hierarchical clusters", J. Chem. Info. Model., 2007, 47, 69-75. [PDF]

  53. F. Zhu*, and D. K. Agrafiotis, "A self-organizing superposition (SOS) algorithm for conformational sampling", J. Comput. Chem., 2007, 28, 1234-1239. [PDF]

  54. D. K. Agrafiotis*, A. Gibbs, F. Zhu, S. Izrailev, and E. Martin, "Conformational sampling of bioactive molecules: a comparative study", J. Chem. Info. Model., 2007, 47, 1067-1086. [PDF]

  55. D. K. Agrafiotis*, D. Bandyopadhyay, J. Wegner, and H. Van Vlijmen, "Recent advances in chemoinformatics", J. Chem. Info. Model., 2007, 47, 1279-1293. [PDF]

  56. F. Zhu*, and D. K. Agrafiotis, "Recursive distance partitioning algorithm for common pharmacophore identification", J. Chem. Info. Model., 2007, 47, 1619-1625. [PDF]

  57. D. K. Agrafiotis*, D. Bandyopadhyay, G. Carta, A. J. S. Knox, and D. G. Lloyd, "On the effects of permuted input on conformational sampling of druglike molecules: an evaluation of stochastic proximity embedding (SPE)", Chem. Biol. Drug Des., 2007, 70(2), 123-133. [PDF]

  58. D. Bandyopadhyay, and D. K. Agrafiotis*, "A self-organizing algorithm for molecular alignment and pharmacophore development", J. Comput. Chem., 2007, in press.

  59. D. K. Agrafiotis*, M. Shemanarev, P. J. Connolly, M. Farnum, and V. S. Lobanov, "SAR maps: a new SAR visualization technique for medicinal chemists", J. Med. Chem., 2007, 50(24), 5926-5937.

  60. D. K. Agrafiotis*, et al., "Advanced Biological and Chemical Discovery (ABCD): centralizing discovery knowledge in an inherently decentralized world", J. Chem. Info. Model., 2007, 47, 1999-2014.


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  1. D. K. Agrafiotis, R. Bone, F. R. Salemme and R. Soll. “System and method for automatically generating chemical compounds with desired properties”. US Patent 5,463,564, October 31, 1995. [USPTO]

  2. D. K. Agrafiotis, R. Bone, F. R. Salemme and R. Soll. “System and method for automatically generating chemical compounds with desired properties”. US Patent 5,574,656, November 12, 1996. [USPTO]

  3. D. K. Agrafiotis, R. Bone, F. R. Salemme and R. Soll. “System, method and computer program for at least partially automatically generating chemical compounds having desired properties”. US Patent 5,684,711, November 4, 1997. [USPTO]

  4. D. K. Agrafiotis, R. Bone, F. R. Salemme and R. Soll. “System, method and computer program for at least partially automatically generating chemical compounds with desired properties from a list of potential chemical compounds to synthesize”. US Patent 5,901,069, May 4, 1999. [USPTO]

  5. D. K. Agrafiotis, and F. R. Salemme. “Method, system, and computer program product for representing similarity/dissimilarity between chemical compounds”. US Patent 6,295,514, September 25,2001. [USPTO]

  6. D. K. Agrafiotis, R. Bone, F. R. Salemme and R. Soll. “System, method and computer program product for identifying chemical compounds with desired properties”. US Patent 6,421,612, July 16,2002. [USPTO]

  7. D. K. Agrafiotis, R. Bone, F. R. Salemme and R. Soll. “Methodof generating chemical compounds having desired properties”. US Patent 6,434,490, August 13,2002. [USPTO]

  8. D. K. Agrafiotis, V. S. Lobanov, and F. R. Salemme. "System, method, and computer program product for representing proximity data in a multidimensional space". US Patent 6,453,246, September 17, 2002. [USPTO]

  9. D. S. Dhanoa, D. Doller, S. Meegalla, R. M. Soll, D. K. Agrafiotis, N. Wisnewski, G. M. Silver, D. T. Stinchcomb, and R. L. Seward. "Use of 1,3-substituted pyrazol-5-yl sulfonates as pesticides". US Patent 6,506,784, January 14, 2003. [USPTO]

  10. S. Meegalla, D. K. Agrafiotis, D. Dhanoa, D. Doller, R. Soll, N. Wisnewski, G. Silver, D. Stinchcomb, R. L. Seward, and D. Sha. "1-aryl-3-thioalkyl pyrazoles, and the synthesis thereof and use thereof as insecticides". US Patent 6,518,266, February 11, 2003. [USPTO]

  11. D. K. Agrafiotis, V. S. Lobanov, and F. R. Salemme. "Method, system and computer program product for nonlinear mapping of multidimensional data". US Patent 6,571,227, May 27, 2003. [USPTO]

  12. D. K. Agrafiotis, V. S. Lobanov, and F. R. Salemme. "Method and computer program product for designing combinatorial arrays". US Patent 6,671,627, December 30, 2003. [USPTO]

  13. D. K. Agrafiotis, V. S. Lobanov, and F. R. Salemme. "Method, system, and computer program product for encoding and building products of a virtual combinatorial library". US Patent 6,678,619, January 13, 2004. [USPTO]

  14. V. S. Lobanov, D. K. Agrafiotis, and F. R. Salemme. "Method, system, and computer program product for determining properties of combinatorial library products from features of library building blocks". US Patent 6,834,239, December 21, 2004. [USPTO]

  15. D. K. Agrafiotis, D. N. Rassokhin, V. S. Lobanov, and F. R. Salemme. "System, method, and computer program product for representing object relationships in a multidimensional space". US Patent 7,039,621, May 2, 2006. [USPTO]

  16. D. K. Agrafiotis, V. S. Lobanov, and F. R. Salemme. "Method, system, and computer program product for analyzing combinatorial libraries". US Patent 7,054,757, June 13, 2006. [USPTO]

  17. D. K. Agrafiotis, V. S. Lobanov, and F. R. Salemme. "Method, system and computer program product for non-linear mapping of multi-dimensional data". US Patent 7,117,187, October 3, 2006. [USPTO]

  18. D. K. Agrafiotis, D. N. Rassokhin, V. S. Lobanov, and F. R. Salemme. "System, method, and computer program product for representing object relationships in a multidimensional space". US Patent 7,139,739, November 21, 2006. [USPTO]
     
     
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