Application of the replacement method as novel variable selection in QSPR. 2. Soil sorption coefficients

• Type: Article in International Scientific Journal
• Date: 2007

Authors

Pablo R Duchowicz (Author) Other; Maykel Perez Gonzalez (Author) Other; Aliuska Morales Helguera (Author) Other; Maria Natalia Dias Soeiro Cordeiro (Author) FCUP; Eduardo A Castro (Author) Other

Journal

Title: Chemometrics and Intelligent Laboratory Systems

Vol. 88

Pages: 197-203

ISSN: 0169-7439

Publisher: Elsevier

Indexing

ISI Web of Knowledge - 29 Citations

Scopus - 35 Citations

Scientific classification

FOS: Engineering and technology > Electrical engineering, Electronic engineering, Information engineering

Other information

Authenticus ID: P-004-7H2

DOI: 10.1016/j.chemolab.2007.05.001

Abstract (EN): We predict the soil sorption coefficients of 163 non-ionic organic pesticides performing a QSPR treatment. A pool containing 1247 theoretical descriptors is explored simultaneously encoding different aspects of the topological, geometrical, and electronic molecular structure. The application of Forward Stepwise Regression, Genetic Algorithms and the Replacement Method leads to an optimal six-parameter equation characterized with R = 0.949 and that also exhibits good cross-validated predictive ability, R(1-25%-O) = 0.916. This model compares fairly well with a previously reported QSPR on the same data set with R=0.904.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 7