Fuzzy clustering analysis of the first 10 MEIC chemicals

被引:15
作者
Sârbu, C
Pop, HF
机构
[1] Univ Babes Bolyai, Fac Chem & Chem Engn, Dept Analyt Chem, RO-3400 Cluj Napoca, Romania
[2] Univ Babes Bolyai, Fac Math & Comp Sci, Dept Comp Sci, RO-3400 Cluj Napoca, Romania
关键词
fuzzy classification; in vivo toxicity tests; in vitro toxicity tests; MEIC chemicals;
D O I
10.1016/S0045-6535(99)00285-4
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
In this paper, we discuss the classification results of the toxicological responses of 32 in vivo and in vitro test systems to the first 10 MEIC chemicals. In this order we have used different fuzzy clustering algorithms, namely hierarchical fuzzy clustering, hierarchical and horizontal fuzzy characteristics clustering and a new clustering technique, namely fuzzy hierarchical cross-classification. The characteristics clustering technique produces fuzzy partitions of the characteristics (chemicals) involved and thus it is a useful tool for studying the (dis)similarities between different chemicals and for essential chemicals selection. The cross-classification algorithm produces not only a fuzzy partition of the test systems analyzed, but also a fuzzy partition of the considered 10 MEIC (multicentre evaluation of in vitro cytotoxicity) chemicals. In this way it is possible to identify which chemicals are responsible for the similarities or differences observed between different groups of test systems. Tn another way, there is a specific sensitivity of a chemical for one or more toxicological tests. (C) 1999 Elsevier Science Ltd. All rights reserved.
引用
收藏
页码:513 / 520
页数:8
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