Prediction of chemical-physical properties by neural networks fro structures
暂无分享,去创建一个
[1] David J. Osguthorpe,et al. Neural network prediction of glass-transition temperatures from monomer structure , 1995 .
[2] Alexandre Arenas,et al. A Fuzzy ARTMAP-Based Quantitative Structure-Property Relationship (QSPR) for the Henry's Law Constant of Organic Compounds , 2003, J. Chem. Inf. Comput. Sci..
[3] Christopher C. Cypcar,et al. A novel approach toward the prediction of the glass transition temperature: Application of the EVM model, a designer QSPR equation for the prediction of acrylate and methacrylate polymers , 1997 .
[4] D. Ranney. Biomimetic transport and rational drug delivery. , 2000, Biochemical pharmacology.
[5] D. W. Noid,et al. On the use of computational neural networks for the prediction of polymer properties , 1996 .
[6] J. Hine,et al. Structural effects on rates and equilibriums. XIX. Intrinsic hydrophilic character of organic compounds. Correlations in terms of structural contributions , 1975 .
[7] M. Altieri,et al. Predicting glass transition temperatures of linear polymers, random copolymers and cured reactive oligomers from chemical structure , 1985 .
[8] Rachel A. Brennan,et al. PREDICTING HENRY'S LAW CONSTANT AND THE EFFECT OF' TEMPERATURE ON HENRY'S LAW CONSTANT , 1997 .
[9] H. Ringsdorf. Structure and properties of pharmacologically active polymers , 1975 .
[10] Alan R. Katritzky,et al. Quantitative Structure-Property Relationship (QSPR) Correlation of Glass Transition Temperatures of High Molecular Weight Polymers , 1998, J. Chem. Inf. Comput. Sci..
[11] W. L. Jorgensen,et al. The OPLS [optimized potentials for liquid simulations] potential functions for proteins, energy minimizations for crystals of cyclic peptides and crambin. , 1988, Journal of the American Chemical Society.
[12] Alessio Micheli,et al. Analysis of the Internal Representations Developed by Neural Networks for Structures Applied to Quantitative Structure-Activity Relationship Studies of Benzodiazepines , 2001, J. Chem. Inf. Comput. Sci..
[13] A. D. McLachlan,et al. Solvation energy in protein folding and binding , 1986, Nature.
[14] J. Platts,et al. Hydrogen bond structural group constants. , 2001, The Journal of organic chemistry.
[15] A. Micheli,et al. A Novel Approach to QSPR/QSAR Based on Neural Networks for Structures , 2003 .
[16] Peter C. Jurs,et al. Prediction of Glass Transition Temperatures from Monomer and Repeat Unit Structure Using Computational Neural Networks , 2002, J. Chem. Inf. Comput. Sci..
[17] Vincenzo Mollica,et al. Group contributions to the thermodynamic properties of non-ionic organic solutes in dilute aqueous solution , 1981 .
[18] U. Kompella. Protein Drug Delivery , 1999 .
[19] Niall J. English,et al. Prediction of Henry's Law Constants by a Quantitative Structure Property Relationship and Neural Networks , 2001, J. Chem. Inf. Comput. Sci..
[20] P. Kollman. Advances and Continuing Challenges in Achieving Realistic and Predictive Simulations of the Properties of Organic and Biological Molecules , 1996 .
[21] Alessandro Sperduti,et al. Supervised neural networks for the classification of structures , 1997, IEEE Trans. Neural Networks.
[22] A. J. Hopfinger,et al. Molecular modelling of polymers: 5. Inclusion of intermolecular energetics in estimating glass and crystal-melt transition temperatures , 1989 .
[23] Hao Zhu,et al. Estimation of the Aqueous Solubility of Organic Molecules by the Group Contribution Approach , 2001, J. Chem. Inf. Comput. Sci..
[24] Polina V. Oliferenko,et al. A General Treatment of Solubility. 1. The QSPR Correlation of Solvation Free Energies of Single Solutes in Series of Solvents , 2003, J. Chem. Inf. Comput. Sci..