13C NMR chemical shift prediction of the sp3 carbon atoms in the α position relative to the double bond in acyclic alkenes

Journal of Chemical Information and Computer Sciences

Volumn 37, Issue 3, 1997, Pages 587-598

  Ivanciuc, O ^a   Rabine, J P ^b   Cabrol Bass, D ^b   Panaye, A ^c   Doucet, J P ^c  

^a UNIVERSITY POLITEHNICA OF BUCHAREST   (Romania)

^b UNIVERSITÉ CÔTE D'AZUR   (France)

^c UNIVERSITÉ PARIS DIDEROT   (France)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 0001308736     PISSN: 00952338     EISSN: None     Source Type: Journal    
DOI: 10.1021/ci9601574     Document Type: Article

References (44)

1. Munk, M. E.; Madison, M. S.; Robb, E. W. The Neural Network as a Tool for Multispectral Interpretation, J. Chem. Inf. Comput. Sci. 1996, 36, 231-238.
2. Fessenden, R. J.; Györgyi, L. Identifying Functional Groups in IR Spectra Using an Artificial Neural Network. J. Chem. Soc., Perkin Trans. 2 1991, 1755-1762.
3. Munk, M. E.; Madison, M. S.; Robb, E. W. Neural Network Models for Infrared Spectrum Interpretation. Mikrochim. Acta 1991, 11, 505-514.
4. Meyer, M.; Wiegelt, T. Interpretation of Infrared Spectra by Artificial Neural Networks. Anal. Chim. Acta 1992, 265, 183-190.
5. Weigel, U.-M.; Herges, R. Automatic Interpretation of Infrared Spectra: Recognition of Aromatic Substitution Patterns Using Neural Networks. J. Chem. Inf. Comput. Sci. 1992, 32, 723-731.
6. Tanabe, K.; Tamura, T.; Uesaka, H. Neural Network System for the Identification of Infrared Spectra. Appl. Spectrosc. 1992, 46, 807-810.
7. Ricard, D.; Cachet, C.; Cabrol-Bass, D.: Forrest, T. P. Neural Network Approach to Structural Feature Recognition from Infrared Spectra. J. Chem. Inf. Comput. Sci. 1993, 33, 202-210.
8. Meyer, M.; Meyer, K.; Hobert, H. Neural Networks for Interpretation of Infrared Spectra Using Extremely Reduced Spectral Data. Anal. Chim. Acta 1993, 282, 407-415.
9. Sbirrazzuoli, N.; Cachet, C.; Cabrol-Bass, D.; Forrest, T. P. Indices for the Evaluation of Neural Network Performance as Classifier: Application to Structural Elucidation in Infrared Spectroscopy. Neural Comput. Applic. 1993, 1, 229-239.
10. Cabrol-Bass, D.; Cachet, C.; Cleva, C.; Eghbaldar, A.; Forrest, T. P. Practical application of neural network research to spectral (infrared and mass) data for structural elucidation. Can. J. Chem. 1995, 73, 1412-1426.
11. Klawun, C.; Wilkins, C. L. Optimization of Functional Group Prediction from Infrared Spectra Using Neural Networks. J. Chem. Inf. Comput. Sci. 1996, 36, 69-81.
12. Curry, B.; Rumelhart, D. E. MSnet: A Neural Network which Classifies Mass Spectra. Tetrahedron Comput. Methodol. 1990, 3, 213-237.
13. Lohninger, H.; Stancl, F. Comparing the Performance of Neural Networks to Well-Established Methods of Multivariate Data Analysis: The Classification of Mass Spectral Data. Fresenius J. Anal. Chem. 1992, 344, 186-189.
14. Werther, W.; Lohninger, H.; Stancl, F.; Varmuza, K. Classification of Mass Spectra. A Comparison of Yes/No Classification Methods for the Recognition of Simple Structural Properties. Chemom. Intell. Lab. Syst. 1994, 22, 63-76.
15. Eghbaldar, A., Forrest, T. P.; Cabrol-Bass, D.; Cambon, A.; Guigonis, J.-M. Identification of Structural Features from Mass Spectrometry Using a Neural Network Approach: Application to Trimethylsilyl Derivatives Used for Medical Diagnosis. J. Chem. Inf. Comput. Sci. 1996, 36, 637-643.
16. Klawun, C.; Wilkins, C. L. Joint Neural Network Interpretation of Infrared and Mass Spectra. J. Chem. Inf. Comput. Sci. 1996, 36, 249-257.
17. Jurs, P. C.; Ball, J. W; Anker, L. S.; Friedman, T. L. Carbon-13 Nuclear Magnetic Resonance Spectrum Simulation. J. Chem. Inf. Comput. Sci. 1992, 32, 272-278.
18. 13C NMR Chemical Shifts. J. Math. Chem. 1991, 6, 63-76.
19. 13C NMR Shift Prediction. J. Chem. Inf. Comput. Sci. 1993, 33, 320-324.
20. 13C NMR Shifts for Methyl Substituted Cyclohexanes. Chemom. Intell. Lab. Syst. 1994, 24, 129-135.
21. 13C NMR Chemical Shifts in Saturated Hydrocarbons. Rev. Roum. Chim. 1995, 40, 1093-1101.
22. 13C NMR Chemical Shifts in a Series of Monosubstituted Benzenes. J. Chem. Inf. Comput. Sci. 1992, 32, 742-747.
23. 13C NMR Chemical Shifts in a Series of Monosubstituted Benzenes. J. Mol. Struct. (Theochem) 1992, 277, 87-107.
24. Anker, L. S.; Jurs, P. C. Prediction of Carbon-13 Nuclear Magnetic Resonance Chemical Shifts by Artificial Neural Networks. Anal. Chem. 1992, 64, 1157-1164.
25. 13C NMR Chemical Shift Data Using Artificial Neural Networks and Partial Least Squares Method J. Mol. Struct. (Theochem) 1994, 311, 241-245.
26. 13C Nuclear Magnetic Spectra of Monosaccharides. J. Chem. Inf. Comput. Sci. 1996, 36, 58-64.
27. 13C Nuclear Magnetic Resonance Spectra of Ribonucleosides Using Multiple Linear Regression Analysis and Neural Networks. J. Chem. Inf. Comput. Sci. 1996, 36, 168-172.
28. 2 Carbon Atoms in Acyclic Alkenes Using Neural Networks. J. Chem. Inf. Comput. Sci. 1996, 36, 644-653.
29. Panaye, A.; Doucet, J. P.; Fan, B. T. Topological Approach of C13 NMR Spectral Simulation: Application to Fuzzy Substructures. J. Chem. Inf. Comput. Sci. 1993, 33, 258-265.
30. Kreinovich, V. Arbitrary Nonlinearity is Sufficient to Represent all Functions by Neural Networks: A Theorem. Neural Networks 1991, 4, 381-384.
31. Bulsari, A. B.; Saxén, H. System Identification of a Biochemical Process Using Feed-Forward Neural Networks. Neurocomputing 1991 3, 125-133.
32. Bulsari, A. B.; Saxén, H. System Identification Using the Symmetric Logarithmoid as an Activation Function in a Feed-Forward Neural Network. Neural Network World 1991, 4, 221-224.
33. Rumelhart, D. E.; Hinton, G. E.; Williams, R. J. Learning Representations by Back-Propagating Errors. Nature 1986, 323, 533-536.
34. Cybenko, G. Approximations by Superpositions of a Sigmoidal Function. Math. Control Signals Syst. 1989, 2, 303-314.
35. Funahashi, K. On the Approximate Realization of Continuous Mappings by Neural Networks. Neural Networks 1989, 2, 183-192.
36. Hornik, K.; Stinchcombe, M.; White, H. Multilayer Feedforward Networks are Universal Approximators. Neural Networks 1989, 2, 359-366.
37. Hornik, K.; Stinchcombe, M.; White, H. Universal Approximation of an Unknown Mapping and Its Derivatives Using Multilayer Feed-forward Networks. Neural Networks 1990, 3, 551-560.
38. 13C -NMR Chemical Shifts of Organic Compounds. Anal. Chim. Acta 1990, 229, 17-25.
39. 3-Hybridized Carbon Atoms in Organic Compounds. Anal. Chim. Acta 1990, 233, 213-222.
40. 2- and sp-Hybridized carbon Atoms in Organic Compounds. Anal. Chim. Acta 1991, 248, 415-428.
41. 13C NMR Spectra Based on an Open Set of Additivity Rules. J. Chem. Inf. Comput. Sci. 1992, 32, 291-295.
42. ChemWindows; SoftShell International, Inc.: 715 Horizon Dr., Ste. 390, Grand Junction, CO 81506-8727.
43. Laidboeur, T.; Laude, I.; Cabrol-Bass, D.; Bangov, I. P. Employment of Fuzzy Information Derived from Spectroscopic Data toward Reducing the Redundancy in the Process of Structure Generation. J. Chem. Inf. Comput. Sci. 1994, 34, 171-178.
44. 13C NMR Spectral Information in the Process of Computer-Aided Structure Elucidation: Estimation of the Carbon Atom Hybridization and α-Environment States. Anal. Chim. Acta 1994, 298, 33-52.