333 related articles for article (PubMed ID: 27640149)
1. 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]
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. Development of binary classification models for assessment of drug-induced liver injury in humans using a large set of FDA-approved drugs.
Zhang H; Zhang HR; Hu ML; Qi HZ
J Pharmacol Toxicol Methods; 2022; 116():107185. PubMed ID: 35623583
[TBL] [Abstract][Full Text] [Related]
4. 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]
5. 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]
6. In Silico Prediction of Drug-Induced Liver Injury Based on Ensemble Classifier Method.
Wang Y; Xiao Q; Chen P; Wang B
Int J Mol Sci; 2019 Aug; 20(17):. PubMed ID: 31443562
[TBL] [Abstract][Full Text] [Related]
7. 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]
8. 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]
9. 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]
10. 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]
11. Prediction of drug-induced eosinophilia adverse effect by using SVM and naïve Bayesian approaches.
Zhang H; Yu P; Xiang ML; Li XB; Kong WB; Ma JY; Wang JL; Zhang JP; Zhang J
Med Biol Eng Comput; 2016 Mar; 54(2-3):361-9. PubMed ID: 26044554
[TBL] [Abstract][Full Text] [Related]
12. 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]
13. Quantitative structure-activity relationship models for predicting drug-induced liver injury based on FDA-approved drug labeling annotation and using a large collection of drugs.
Chen M; Hong H; Fang H; Kelly R; Zhou G; Borlak J; Tong W
Toxicol Sci; 2013 Nov; 136(1):242-9. PubMed ID: 23997115
[TBL] [Abstract][Full Text] [Related]
14. 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]
15. A predictive ligand-based Bayesian model for human drug-induced liver injury.
Ekins S; Williams AJ; Xu JJ
Drug Metab Dispos; 2010 Dec; 38(12):2302-8. PubMed ID: 20843939
[TBL] [Abstract][Full Text] [Related]
16. Prediction models for drug-induced hepatotoxicity by using weighted molecular fingerprints.
Kim E; Nam H
BMC Bioinformatics; 2017 May; 18(Suppl 7):227. PubMed ID: 28617228
[TBL] [Abstract][Full Text] [Related]
17. In Vitro Drug-Induced Liver Injury Prediction: Criteria Optimization of Efflux Transporter IC50 and Physicochemical Properties.
Yucha RW; He K; Shi Q; Cai L; Nakashita Y; Xia CQ; Liao M
Toxicol Sci; 2017 Jun; 157(2):487-499. PubMed ID: 28369588
[TBL] [Abstract][Full Text] [Related]
18. The Liver Toxicity Knowledge Base (LKTB) and drug-induced liver injury (DILI) classification for assessment of human liver injury.
Thakkar S; Chen M; Fang H; Liu Z; Roberts R; Tong W
Expert Rev Gastroenterol Hepatol; 2018 Jan; 12(1):31-38. PubMed ID: 28931315
[TBL] [Abstract][Full Text] [Related]
19. A high content screening assay to predict human drug-induced liver injury during drug discovery.
Persson M; Løye AF; Mow T; Hornberg JJ
J Pharmacol Toxicol Methods; 2013; 68(3):302-13. PubMed ID: 23933113
[TBL] [Abstract][Full Text] [Related]
20. Predicting Drug-Induced Liver Injury Using Ensemble Learning Methods and Molecular Fingerprints.
Ai H; Chen W; Zhang L; Huang L; Yin Z; Hu H; Zhao Q; Zhao J; Liu H
Toxicol Sci; 2018 Sep; 165(1):100-107. PubMed ID: 29788510
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]