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Performance evaluation of CAESAR–QSAR output using PAHs as a case study
Author(s) -
Vračko Marjan,
Bobst Sol
Publication year - 2014
Publication title -
journal of chemometrics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.47
H-Index - 92
eISSN - 1099-128X
pISSN - 0886-9383
DOI - 10.1002/cem.2578
Subject(s) - quantitative structure–activity relationship , principal component analysis , cluster analysis , hierarchical clustering , similarity (geometry) , computer science , data mining , set (abstract data type) , molecular descriptor , chemistry , artificial intelligence , machine learning , image (mathematics) , programming language
The set of 16 polycyclic aromatic hydrocarbon compounds was examined with the Internet available quantitative structure–activity relationship (QSAR) CAESAR models. For mutagenicity, carcinogenicity, developmental toxicity, and skin sensitization, the report includes the predicted classifications, the analysis of applicability domains, and the similarity sets, which consist of the similar compounds from the training sets. These results were further analyzed with chemometrical methods, that is, hierarchical clustering, principal component analysis, and self‐organizing maps, which were used for clustering and to define the cluster indicators. Such analysis assists the users in planning the application of QSAR models for hazard communication in regulatory compliance and in research of new active compounds. Copyright © 2013 John Wiley & Sons, Ltd.