Statistical approaches to estimating the relative contribution of intermolecular interactions in aliphatic alcohols: Application to QSPR/QSAR modeling of their boiling points

Chemical Product and Process Modeling

Volumn 4, Issue 1, 2009, Pages

  Nohair, Mohamed ^a,b   Mallouk, Noura ^a   Benmarzouk, Marouane ^a   Mohssine, El Morrakchi ^a  

^a HASSAN II UNIVERSITY   (Morocco)

^b HASSAN II UNIVERSITY OF CASABLANCA   (Morocco)

Author keywords

Aliphatic alcohols; Multifunctional autocorrelation method; Neural network; Weight partitioning method

Indexed keywords

ALIPHATIC ALCOHOLS; DATA SETS; DESCRIPTORS; ERROR BACK PROPAGATION ALGORITHMS; FEED-FORWARD NEURAL NETWORKS; GENERAL DESCRIPTIONS; INPUT FACTORS; INTER-MOLECULAR INTERACTIONS; INTERMOLECULAR FORCES; LEVENBERG-MARQUARDT; LINEAR MODELS; LOCAL DESCRIPTIONS; MOLECULAR DESCRIPTORS; MULTIFUNCTIONAL AUTOCORRELATION METHOD; POLAR INTERACTIONS; REGRESSION COEFFICIENTS; RELATIVE CONTRIBUTIONS; STATISTICAL APPROACHES; THREE LAYERS; TOPOLOGICAL DESCRIPTIONS; VARIABLE ANALYSIS; WEIGHT PARTITIONING METHOD;

BACKPROPAGATION; BACKPROPAGATION ALGORITHMS; CHEMICAL BONDS; CORRELATION DETECTORS; FISCHER-TROPSCH SYNTHESIS; MOLECULES; NEURAL NETWORKS; ROUGH SET THEORY; VAN DER WAALS FORCES;

BOILING POINT;

EID: 62649143852     PISSN: 19342659     EISSN: None     Source Type: Journal    
DOI: 10.2202/1934-2659.1274     Document Type: Article

References (21)

1. Basheer I.A., Najaar Y.M. and Hajmer M.N. (1996). (Neuronet Modeling of VOC Adsorption by GAC) Environ. Technol., 17, 795.
2. Burns J.A. and Whitesides G.M. (1993), Feed-forward neural networks in chemistry: mathematical systems for classification and pattern recognition, Chem. Rev., 93, 8, 2591.
3. Devillers J. (1996), Neural Networks in QSAR and Drug Design, Academic Press, London.
4. evillers J., Domine D. and Guilon C. (1998), Autocorrelation modeling of lipophilicity with a back-propagation neural network, Eur. J Med. Chem., 33, 659.
5. Dreyfus G., Martinez J., Samuelides M., Gordon M., Badran F., Thiria S. and Hérault L. (2002), Réseaux de neurones - Méthodologie et applications, Edition Eyrolles.
6. Estrada E. and Molina E. (2001), Novel Local (fragment-based) Topological Molecular Descriptors for QSPR/QSAR and Molecular Design, J. Mol. Grap. Mod., 20, 54.
7. Galvez J., Garcia R., Salabert M. T. and Soler R. (1994), Charge Indexes. New Topological Descriptors, J. Chem. Inf. Comput. Sci., 34, 520.
8. Garson G.D. (1991), Interpreting Neural-Network Connection Weights, AI Expert, 6, 47.
9. Hagan M.T. and Menhaj M.B. (1995), Training Feed-forward Networks with the Marquardt. Algorithm, IEEE Trans. Neural Networks, 5(6), 989-993.
10. Hassoum M.H. (1995), Fundamentals of artificial neural networks. Eds., MIT Press, Cambridge.
11. Haykin S. (1994), Neural networks: a comprehensive foundation, Mac-Millan, New York.
12. Kier L. B. and Hall L. H. (1999), Molecular Structure Description. The Electrotopological State; Academic Press: New York.
13. Katritzky A.R. and Gordeeva E. (1993), Traditional topological indices vs electronic, geometrical, and combined molecular descriptors in QSAR/QSPR research, J. Chem. Inf. Comput. Sci., 33, 835.
14. MATLAB 7.0, The MathWorks, Inc., Natick, MA., (2002).
15. Nohair M. and Zakarya D. (2003), Prediction of solubility of aliphatic alcohols using the restricted components of autocorrelation method (RCAM), J. Mol. Model., 9, 365.
16. Nohair M., Zakarya D., Berrada A. (2002), Autocorrelation Method Adapted To Generate New Atomic Environments: Application for the Prediction of 13-C Chemical Shifts of Alkanes, J. Chem. Inf. Comput. Sci., 42, 586.
17. Olivero J., Gracia T., Payares P., Vivas R., Diaz D., Daza E. and Geerlings P. (1997), Molecular structure and gas chromatographic retention behavior of the components of Ylang-Ylang oil, J. Pharm. Sci., 86 (5), 625.
18. Ren B. (2002), Novel atomic-level-based AI topological descriptors: application to QSPR/QSAR modelling, J. Chem. Inf. Comput. Sci., 42, 858.
19. Rudolph S. (1997), On topology, size and generalization of non-linear feedforward neural networks, Neurocomputing, 16, 1.
20. Yao Y.-Y., Xu L., Yang Y.-Q. and Yuan X. S. (1993), Study on Structure- Activity Relationships of Organic Compounds. 3. New Topological Indices and Their Applications, J. Chem. Inf. Comput. Sci., 33, 590.
21. Zupan J. and Gasteiger J. (1997), Neural Networks for Chemistry and Drug Design. Wiley-VCH, Weinheim, Germany.