These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.
156 related articles for article (PubMed ID: 28232239)
1. Novel naïve Bayes classification models for predicting the chemical Ames mutagenicity. Zhang H; Kang YL; Zhu YY; Zhao KX; Liang JY; Ding L; Zhang TG; Zhang J Toxicol In Vitro; 2017 Jun; 41():56-63. PubMed ID: 28232239 [TBL] [Abstract][Full Text] [Related]
2. Development of novel prediction model for drug-induced mitochondrial toxicity by using naïve Bayes classifier method. Zhang H; Yu P; Ren JX; Li XB; Wang HL; Ding L; Kong WB Food Chem Toxicol; 2017 Dec; 110():122-129. PubMed ID: 29042293 [TBL] [Abstract][Full Text] [Related]
3. Novel naïve Bayes classification models for predicting the carcinogenicity of chemicals. Zhang H; Cao ZX; Li M; Li YZ; Peng C Food Chem Toxicol; 2016 Nov; 97():141-149. PubMed ID: 27597133 [TBL] [Abstract][Full Text] [Related]
4. Development and evaluation of in silico prediction model for drug-induced respiratory toxicity by using naïve Bayes classifier method. Zhang H; Ma JX; Liu CT; Ren JX; Ding L Food Chem Toxicol; 2018 Nov; 121():593-603. PubMed ID: 30261216 [TBL] [Abstract][Full Text] [Related]
5. Development of novel in silico model for developmental toxicity assessment by using naïve Bayes classifier method. Zhang H; Ren JX; Kang YL; Bo P; Liang JY; Ding L; Kong WB; Zhang J Reprod Toxicol; 2017 Aug; 71():8-15. PubMed ID: 28428071 [TBL] [Abstract][Full Text] [Related]
6. Predicting drug-induced liver injury in human with Naïve Bayes classifier approach. Zhang H; Ding L; Zou Y; Hu SQ; Huang HG; Kong WB; Zhang J J Comput Aided Mol Des; 2016 Oct; 30(10):889-898. PubMed ID: 27640149 [TBL] [Abstract][Full Text] [Related]
7. Development of an in silico prediction model for chemical-induced urinary tract toxicity by using naïve Bayes classifier. Zhang H; Ren JX; Ma JX; Ding L Mol Divers; 2019 May; 23(2):381-392. PubMed ID: 30294757 [TBL] [Abstract][Full Text] [Related]
8. In silico prediction of chemical Ames mutagenicity. Xu C; Cheng F; Chen L; Du Z; Li W; Liu G; Lee PW; Tang Y J Chem Inf Model; 2012 Nov; 52(11):2840-7. PubMed ID: 23030379 [TBL] [Abstract][Full Text] [Related]
9. A comparative study of support vector machine, artificial neural network and bayesian classifier for mutagenicity prediction. Sharma A; Kumar R; Varadwaj PK; Ahmad A; Ashraf GM Interdiscip Sci; 2011 Sep; 3(3):232-9. PubMed ID: 21956745 [TBL] [Abstract][Full Text] [Related]
10. Developing novel computational prediction models for assessing chemical-induced neurotoxicity using naïve Bayes classifier technique. Zhang H; Mao J; Qi HZ; Xie HZ; Shen C; Liu CT; Ding L Food Chem Toxicol; 2020 Sep; 143():111513. PubMed ID: 32621845 [TBL] [Abstract][Full Text] [Related]
11. In silico prediction of drug-induced myelotoxicity by using Naïve Bayes method. Zhang H; Yu P; Zhang TG; Kang YL; Zhao X; Li YY; He JH; Zhang J Mol Divers; 2015 Nov; 19(4):945-53. PubMed ID: 26162532 [TBL] [Abstract][Full Text] [Related]
12. Derivation and validation of toxicophores for mutagenicity prediction. Kazius J; McGuire R; Bursi R J Med Chem; 2005 Jan; 48(1):312-20. PubMed ID: 15634026 [TBL] [Abstract][Full Text] [Related]
13. Developing novel in silico prediction models for assessing chemical reproductive toxicity using the naïve Bayes classifier method. Zhang H; Shen C; Liu RZ; Mao J; Liu CT; Mu B J Appl Toxicol; 2020 Sep; 40(9):1198-1209. PubMed ID: 32207182 [TBL] [Abstract][Full Text] [Related]
14. Development of novel in silico prediction model for drug-induced ototoxicity by using naïve Bayes classifier approach. Zhang H; Liu CT; Mao J; Shen C; Xie RL; Mu B Toxicol In Vitro; 2020 Jun; 65():104812. PubMed ID: 32109528 [TBL] [Abstract][Full Text] [Related]
15. A novel QSAR model of Salmonella mutagenicity and its application in the safety assessment of drug impurities. Valencia A; Prous J; Mora O; Sadrieh N; Valerio LG Toxicol Appl Pharmacol; 2013 Dec; 273(3):427-34. PubMed ID: 24090816 [TBL] [Abstract][Full Text] [Related]
16. Multiple Instance Learning Improves Ames Mutagenicity Prediction for Problematic Molecular Species. Feeney SV; Lui R; Guan D; Matthews S Chem Res Toxicol; 2023 Aug; 36(8):1227-1237. PubMed ID: 37477941 [TBL] [Abstract][Full Text] [Related]
17. A knowledge-based expert rule system for predicting mutagenicity (Ames test) of aromatic amines and azo compounds. Gadaleta D; Manganelli S; Manganaro A; Porta N; Benfenati E Toxicology; 2016 Aug; 370():20-30. PubMed ID: 27644887 [TBL] [Abstract][Full Text] [Related]
18. Computational identification of structural factors affecting the mutagenic potential of aromatic amines: study design and experimental validation. Slavov SH; Stoyanova-Slavova I; Mattes W; Beger RD; Brüschweiler BJ Arch Toxicol; 2018 Jul; 92(7):2369-2384. PubMed ID: 29779177 [TBL] [Abstract][Full Text] [Related]
20. Prediction on the mutagenicity of nitroaromatic compounds using quantum chemistry descriptors based QSAR and machine learning derived classification methods. Hao Y; Sun G; Fan T; Sun X; Liu Y; Zhang N; Zhao L; Zhong R; Peng Y Ecotoxicol Environ Saf; 2019 Dec; 186():109822. PubMed ID: 31634658 [TBL] [Abstract][Full Text] [Related] [Next] [New Search]