https://scholars.lib.ntu.edu.tw/handle/123456789/632251
標題: | Categorical QSAR models for skin sensitization based upon local lymph node assay classification measures Part 2: 4D-Fingerprint three-State and Two-2-State logistic regression models | 作者: | Li Y Pan D Liu J Kern P.S Gerberick G.F Hopfinger A.J YUFENG JANE TSENG |
關鍵字: | 4D-fingerprints; Categorical models; QSAR, logistic regression; Skin sensitization | 公開日期: | 2007 | 卷: | 99 | 期: | 2 | 起(迄)頁: | 532-544 | 來源出版物: | Toxicological Sciences | 摘要: | Three and four state categorical quantitative structure-activity relationship (QSAR) models for skin sensitization have been constructed using data from the murine Local Lymph Node Assay studies. These are the same data we previously used to build two-state (sensitizer, nonsensitizer) QSAR models (Li et al., 2007, Chem. Res. Toxicol. 20, 114-128). 4D-fingerprint descriptors derived from the 4D-molecular similarity paradigm are used to generate these models. A training set of 196 and a test set of 22 structurally diverse compounds were used in this study. Logistic regression, and partial least square coupled logistic regression were used to build the models. The three-state QSAR model gives a classification accuracy of 73.4% for the training set and 63.6% for the test set, while the random average value of classification accuracy for any three-state data set is 33.3%. The two-2-state [four categories in total] QSAR model gives a classification accuracy of 83.2% for the training set and 54.6% for the test set, while the random average value of classification accuracy for any two-2-state data set is 25%. An analysis of the skin-sensitization models developed in this study, as well as the two-state QSAR models developed in our previous analysis, suggests that the "moderate" sensitizers may be the main source of limited model accuracy. © The Author 2007. Published by Oxford University Press on behalf of the Society of Toxicology. All rights reserved. |
URI: | https://www.scopus.com/inward/record.uri?eid=2-s2.0-38449115068&doi=10.1093%2ftoxsci%2fkfm185&partnerID=40&md5=f3e509f2828043e63def7a77cfc8c87b https://scholars.lib.ntu.edu.tw/handle/123456789/632251 |
ISSN: | 10966080 | DOI: | 10.1093/toxsci/kfm185 | SDG/關鍵字: | 1 (para methoxyphenyl) 1 penten 3 one; 1 iodononane; 1 iodooctadecane; 1 iodotetradecane; 1 naphthol; 1 phenyl 1,2 propanedione; 1 phenyl 2 methylbutane 1,3 dione; 1,2 benzisothiazolin 3 one; 1,2,4 benzenetricarboxylic anhydride (trimellitic anhydride); 12 bromo decanol; 12 bromododecanoic acid; 2 acetylcyclohexanenone; 2 amino 6 chloro 4 nitrophenol; 2 aminophenol; 2 bromo 2 bromomethylglutaronitrile; 2 bromotetradecanoic acid; 2 ethylbutaldehyde; 2 hydroxyethylacrylate; 2 hydroxypropylmethacrylate; 2 mercaptobenzothiazole; 2 methyl 4 isothiazolin 3 one; 2 methyl 5 hydroxyethylaminophenol; 2 nitro 1,4 phenylenediamine; 2,2,6,6 tetramethylheptane 3,5 dione; 2,3 butanedione; butanol; chemical compound; creosol; methylnitronitrosoguanidine; accuracy; animal model; article; classification algorithm; controlled study; data extraction; finger dermatoglyphics; local lymph node assay; logistic regression analysis; molecular dynamics; molecular systematics; mouse; nonhuman; quantitative structure property relation; skin sensitization; statistical model; toxicity testing; animal; drug effect; guinea pig; lymph node; quantitative structure activity relation; skin; toxicity testing; Murinae; Animals; Guinea Pigs; Logistic Models; Lymph Nodes; Quantitative Structure-Activity Relationship; Skin; Toxicity Tests |
顯示於: | 資訊工程學系 |
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