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Authors

  • Joseph R. Votano,
  • Marc Parham,
  • Lowell H. Hall,
  • Lemont B. Kier,
  • L. Mark Hall
  • DOI:10.1002/cbdv.200490137

Citing Literature

  • Number of times cited: 27
  1. 1Erno Lehtinen, Minna Hannula-Sormunen, Jake McMullen, Hans Gruber, Cultivating mathematical skills: from drill-and-practice to deliberate practice, ZDM, 2017CrossRef
  2. 2Dharmendra Yadav, Reeta Rai, Ramendra Pratap, Harpreet Singh, Chemometrics Applications and Research, 2016, 33CrossRef
  3. 3Abdul Rafiq Ab Razak, Norshuhaila Mohamed Sunar, Nurul Azira Alias, Paran Gani, Menega Subramaniam, N. Abd Rahman, Z. Mohd Jaini, R. Yunus, S.N. Rahmat, Physiochemicals and Heavy Metal Removal from Domestic Wastewater via Phycoremediation, MATEC Web of Conferences, 2016, 47, 05003CrossRef
  4. 4Bianca M. Blunden, Martina H. Stenzel, Incorporating ruthenium into advanced drug delivery carriers - an innovative generation of chemotherapeutics, Journal of Chemical Technology & Biotechnology, 2015, 90, 7, 1177Wiley Online Library
  5. 5Hong Zhi Li, Lin Li, Zi Yan Zhong, Yi Han, LiHong Hu, Ying Hua Lu, An Accurate and Efficient Method to Predict Y-NO Bond Homolysis Bond Dissociation Energies, Mathematical Problems in Engineering, 2013, 2013, 1CrossRef
  6. 6Maryam Salahinejad, Tu C. Le, David A. Winkler, Aqueous Solubility Prediction: Do Crystal Lattice Interactions Help?, Molecular Pharmaceutics, 2013, 10, 7, 2757CrossRef
  7. 7David Hecht, Applications of machine learning and computational intelligence to drug discovery and development, Drug Development Research, 2011, 72, 1, 53Wiley Online Library
  8. 8Farhad Gharagheizi, Ali Eslamimanesh, Amir H. Mohammadi, Dominique Richon, Representation/Prediction of Solubilities of Pure Compounds in Water Using Artificial Neural Network−Group Contribution Method, Journal of Chemical & Engineering Data, 2011, 56, 4, 720CrossRef
  9. 9Dong-Sheng Cao, Qing-Song Xu, Yi-Zeng Liang, Xian Chen, Hong-Dong Li, Prediction of aqueous solubility of druglike organic compounds using partial least squares, back-propagation network and support vector machine, Journal of Chemometrics, 2010, n/aWiley Online Library
  10. 10Paulo Paixão, Luís F. Gouveia, José A.G. Morais, Prediction of the in vitro permeability determined in Caco-2 cells by using artificial neural networks, European Journal of Pharmaceutical Sciences, 2010, 41, 1, 107CrossRef
  11. 11Sandhya Kortagere, Sean Ekins, Troubleshooting computational methods in drug discovery, Journal of Pharmacological and Toxicological Methods, 2010, 61, 2, 67CrossRef
  12. 12Christian Kramer, Tilmann Heinisch, Thilo Fligge, Bernd Beck, Timothy Clark, A Consistent Dataset of Kinetic Solubilities for Early-Phase Drug Discovery, ChemMedChem, 2009, 4, 9, 1529Wiley Online Library
  13. 13Tzipporah M. Kertesz, Lowell H. Hall, Dennis W. Hill, David F. Grant, CE50: Quantifying collision induced dissociation energy for small molecule characterization and identification, Journal of the American Society for Mass Spectrometry, 2009, 20, 9, 1759CrossRef
  14. 14Paulo Paixão, Luís F. Gouveia, José A.G. Morais, Prediction of drug distribution within blood, European Journal of Pharmaceutical Sciences, 2009, 36, 4-5, 544CrossRef
  15. 15Hui Zhang, Ming-Li Xiang, Chang-Ying Ma, Qi Huang, Wei Li, Yang Xie, Yu-Quan Wei, Sheng-Yong Yang, Three-class classification models of logS and logP derived by using GA–CG–SVM approach, Molecular Diversity, 2009, 13, 2, 261CrossRef
  16. 16Junmei Wang, Tingjun Hou, , 2009, 5, 101CrossRef
  17. 17Thorsteinn Loftsson, Marcus E. Brewster, Physicochemical properties of water and its effect on drug delivery, International Journal of Pharmaceutics, 2008, 354, 1-2, 248CrossRef
  18. 18D Rognan, Chemogenomic approaches to rational drug design, British Journal of Pharmacology, 2007, 152, 1, 38Wiley Online Library
  19. 19L.H. Hall, L.B. Kier, L.M. Hall, Comprehensive Medicinal Chemistry II, 2007, 537CrossRef
  20. 20J. Taskinen, U. Norinder, Comprehensive Medicinal Chemistry II, 2007, 627CrossRef