Title Classification models for neocryptolepine derivatives as inhibitors of the $\beta$-haematin formation Author Dejaegher, B. Dhooghe, L. Goodarzi, M. Apers, S. Pieters, L. Heyden, Vander, Y. Faculty/Department Faculty of Pharmaceutical, Biomedical and Veterinary Sciences. Pharmacy Publication type article Publication 2011 Amsterdam , 2011 Subject Pharmacology. Therapy Source (journal) Analytica chimica acta. - Amsterdam Volume/pages 705(2011) :1/2 , p. 98-110 ISSN 0003-2670 ISI 000295993900014 Carrier E Target language English (eng) Full text (Publishers DOI) Affiliation University of Antwerp 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. E-info https://repository.uantwerpen.be/docman/iruaauth/0a34d7/599a1659453.pdf http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000295993900014&DestLinkType=RelatedRecords&DestApp=ALL_WOS&UsrCustomerID=ef845e08c439e550330acc77c7d2d848 http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000295993900014&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=ef845e08c439e550330acc77c7d2d848 http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000295993900014&DestLinkType=CitingArticles&DestApp=ALL_WOS&UsrCustomerID=ef845e08c439e550330acc77c7d2d848 Handle