Publication
Title
Classification models for neocryptolepine derivatives as inhibitors of the -haematin formation
Author
Abstract
This paper describes the construction of a QSAR model to relate the structures of various derivatives of neocryptolepine to their anti-malarial activities. QSAR classification models were build using Linear Discriminant Analysis (LDA), Quadratic Discriminant Analysis (QDA), Classification and Regression Trees (CART), Partial Least Squares Discriminant Analysis (PLS-DA), Orthogonal Projections to Latent Structures Discriminant Analysis (OPLS-DA), and Support Vector Machines for Classification (SVM-C), using four sets of molecular descriptors as explanatory variables. Prior to classification, the molecules were divided into a training and a test set using the duplex algorithm. The different classification models were compared regarding their predictive ability, simplicity, and interpretability. Both binary and multi-class classification models were constructed. For classification into three classes, CART and One-Against-One (OAO)-SVM-C were found to be the best predictive methods, while for classification into two classes, LDA, QDA and CART were.
Language
English
Source (journal)
Analytica chimica acta. - Amsterdam
Publication
Amsterdam : 2011
ISSN
0003-2670
Volume/pages
705:1/2(2011), p. 98-110
ISI
000295993900014
Full text (Publisher's DOI)
Full text (publisher's version - intranet only)
UAntwerpen
Faculty/Department
Research group
Publication type
Subject
Affiliation
Publications with a UAntwerp address
External links
Web of Science
Record
Identification
Creation 14.01.2012
Last edited 14.06.2017
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