Classification models for neocryptolepine derivatives as inhibitors of the β-haematin formation
[Display omitted] ► Classification of various neocryptolepine derivatives according to their anti-malarial activity. ► Use of LDA, QDA, CART, PLS-DA, OPLS-DA, OAO-SVM-C, and OAA-SVM-C for classification. ► CART model preferred for three-class classification according to activity. ► LDA and QDA model...
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Published in | Analytica chimica acta Vol. 705; no. 1; pp. 98 - 110 |
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Main Authors | , , , , , |
Format | Journal Article Conference Proceeding |
Language | English |
Published |
Amsterdam
Elsevier B.V
31.10.2011
Elsevier |
Subjects | |
Online Access | Get full text |
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Summary: | [Display omitted]
► Classification of various neocryptolepine derivatives according to their anti-malarial activity. ► Use of LDA, QDA, CART, PLS-DA, OPLS-DA, OAO-SVM-C, and OAA-SVM-C for classification. ► CART model preferred for three-class classification according to activity. ► LDA and QDA models preferred for two-class classification according to activity.
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. |
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Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 |
ISSN: | 0003-2670 1873-4324 |
DOI: | 10.1016/j.aca.2011.04.019 |