Int. J. Mol. Sci. 2007, 8(4), 335-345; doi:10.3390/i8040335
Article

How Good Can the Characteristic Polynomial Be for Correlations?

1,* email and 2email
Received: 14 January 2007; in revised form: 27 March 2007 / Accepted: 12 April 2007 / Published: 30 April 2007
(This article belongs to the Special Issue Interaction of Biological Molecules)
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Abstract: The aim of this study was to investigate the characteristic polynomials resulting from the molecular graphs used as molecular descriptors in the characterization of the properties of chemical compounds. A formal calculus method is proposed in order to identify the value of the characteristic polynomial parameters for which the extremum values of the squared correlation coefficient are obtained in univariate regression models. The developed calculation algorithm was applied to a sample of nonane isomers. The obtained results revealed that the proposed method produced an accurate and unique solution for the best relationship between the characteristic polynomial as molecular descriptor and the property of interest.
Keywords: Characteristic polynomial; Graph theory; Structure-Property Relationships; Nonane isomers; Henry’s law constant (solubility).
PDF Full-text Download PDF Full-Text [83 KB, uploaded 19 June 2014 00:05 CEST]

Export to BibTeX |
EndNote


MDPI and ACS Style

Bolboaca, S.D.; Jantschi, L. How Good Can the Characteristic Polynomial Be for Correlations? Int. J. Mol. Sci. 2007, 8, 335-345.

AMA Style

Bolboaca SD, Jantschi L. How Good Can the Characteristic Polynomial Be for Correlations? International Journal of Molecular Sciences. 2007; 8(4):335-345.

Chicago/Turabian Style

Bolboaca, Sorana D.; Jantschi, Lorentz. 2007. "How Good Can the Characteristic Polynomial Be for Correlations?" Int. J. Mol. Sci. 8, no. 4: 335-345.

Int. J. Mol. Sci. EISSN 1422-0067 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert