Acquiring decision rules for predicting ames-negative hepatocarcinogens using chemical-chemical interactions

研究成果: 書貢獻/報告類型會議貢獻

5 引文 (Scopus)

摘要

Chemical carcinogenicity is an important safety issue for the evaluation of drugs and environmental pollutants. The Ames test is useful for detecting genotoxic hepatocarcinogens. However, the assessment of Ames-negative hepatocarcinogens depends on 2-year rodent bioassays. Alternative methods are desirable for the efficient identification of Ames-negative hepatocarcinogens. This study proposed a decision tree-based method using chemical-chemical interaction information for predicting hepatocarcinogens. It performs much better than that using molecular descriptors with accuracies of 86% and 76% for validation and independent test, respectively. Four important interacting chemicals with interpretable decision rules were identified and analyzed. With the high prediction performances, the acquired decision rules based on chemical-chemical interactions provide a useful prediction method and better understanding of Ames-negative hepatocarcinogens.

原文英語
主出版物標題Pattern Recognition in Bioinformatics - 9th IAPR International Conference, PRIB 2014, Proceedings
發行者Springer Verlag
頁面1-9
頁數9
ISBN(列印)9783319091914
DOIs
出版狀態已發佈 - 一月 1 2014
對外發佈Yes
事件9th IAPR International Conference on Pattern Recognition in Bioinformatics, PRIB 2014 - Stockholm, 瑞典
持續時間: 八月 21 2014八月 23 2014

出版系列

名字Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
8626 LNBI
ISSN(列印)0302-9743
ISSN(電子)1611-3349

會議

會議9th IAPR International Conference on Pattern Recognition in Bioinformatics, PRIB 2014
國家瑞典
城市Stockholm
期間8/21/148/23/14

指紋

Decision Rules
Interaction
Bioassay
Molecular Descriptors
Decision trees
Performance Prediction
Pollutants
Decision tree
Drugs
Safety
Prediction
Alternatives
Evaluation

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

引用此文

Tung, C. W. (2014). Acquiring decision rules for predicting ames-negative hepatocarcinogens using chemical-chemical interactions. 於 Pattern Recognition in Bioinformatics - 9th IAPR International Conference, PRIB 2014, Proceedings (頁 1-9). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); 卷 8626 LNBI). Springer Verlag. https://doi.org/10.1007/978-3-319-09192-1_1

Acquiring decision rules for predicting ames-negative hepatocarcinogens using chemical-chemical interactions. / Tung, Chun Wei.

Pattern Recognition in Bioinformatics - 9th IAPR International Conference, PRIB 2014, Proceedings. Springer Verlag, 2014. p. 1-9 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); 卷 8626 LNBI).

研究成果: 書貢獻/報告類型會議貢獻

Tung, CW 2014, Acquiring decision rules for predicting ames-negative hepatocarcinogens using chemical-chemical interactions. 於 Pattern Recognition in Bioinformatics - 9th IAPR International Conference, PRIB 2014, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 卷 8626 LNBI, Springer Verlag, 頁 1-9, 9th IAPR International Conference on Pattern Recognition in Bioinformatics, PRIB 2014, Stockholm, 瑞典, 8/21/14. https://doi.org/10.1007/978-3-319-09192-1_1
Tung CW. Acquiring decision rules for predicting ames-negative hepatocarcinogens using chemical-chemical interactions. 於 Pattern Recognition in Bioinformatics - 9th IAPR International Conference, PRIB 2014, Proceedings. Springer Verlag. 2014. p. 1-9. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). https://doi.org/10.1007/978-3-319-09192-1_1
Tung, Chun Wei. / Acquiring decision rules for predicting ames-negative hepatocarcinogens using chemical-chemical interactions. Pattern Recognition in Bioinformatics - 9th IAPR International Conference, PRIB 2014, Proceedings. Springer Verlag, 2014. 頁 1-9 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
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