163 related articles for article (PubMed ID: 15370419)
1. Using fragment chemistry data mining and probabilistic neural networks in screening chemicals for acute toxicity to the fathead minnow.
Niculescu SP; Atkinson A; Hammond G; Lewis M
SAR QSAR Environ Res; 2004 Aug; 15(4):293-309. PubMed ID: 15370419
[TBL] [Abstract][Full Text] [Related]
2. Probabilistic neural networks modeling of the 48-h LC50 acute toxicity endpoint to Daphnia magna.
Niculescu SP; Lewis MA; Tigner J
SAR QSAR Environ Res; 2008; 19(7-8):735-50. PubMed ID: 19061086
[TBL] [Abstract][Full Text] [Related]
3. Validation of a QSAR model for acute toxicity.
Pavan M; Netzeva TI; Worth AP
SAR QSAR Environ Res; 2006 Apr; 17(2):147-71. PubMed ID: 16644555
[TBL] [Abstract][Full Text] [Related]
4. Statistically validated QSARs, based on theoretical descriptors, for modeling aquatic toxicity of organic chemicals in Pimephales promelas (fathead minnow).
Papa E; Villa F; Gramatica P
J Chem Inf Model; 2005; 45(5):1256-66. PubMed ID: 16180902
[TBL] [Abstract][Full Text] [Related]
5. Prediction of fathead minnow acute toxicity of organic compounds from molecular structure.
Eldred DV; Weikel CL; Jurs PC; Kaiser KL
Chem Res Toxicol; 1999 Jul; 12(7):670-8. PubMed ID: 10409408
[TBL] [Abstract][Full Text] [Related]
6. An automated group contribution method in predicting aquatic toxicity: the diatomic fragment approach.
Casalegno M; Benfenati E; Sello G
Chem Res Toxicol; 2005 Apr; 18(4):740-6. PubMed ID: 15833034
[TBL] [Abstract][Full Text] [Related]
7. Using probabilistic neural networks to model the toxicity of chemicals to the fathead minnow (Pimephales promelas): a study based on 865 compounds.
Kaiser KL; Niculescu SP
Chemosphere; 1999 Jun; 38(14):3237-45. PubMed ID: 10390840
[TBL] [Abstract][Full Text] [Related]
8. Validation of counter propagation neural network models for predictive toxicology according to the OECD principles: a case study.
Vracko M; Bandelj V; Barbieri P; Benfenati E; Chaudhry Q; Cronin M; Devillers J; Gallegos A; Gini G; Gramatica P; Helma C; Mazzatorta P; Neagu D; Netzeva T; Pavan M; Patlewicz G; Randić M; Tsakovska I; Worth A
SAR QSAR Environ Res; 2006 Jun; 17(3):265-84. PubMed ID: 16815767
[TBL] [Abstract][Full Text] [Related]
9. Predicting acute aquatic toxicity of structurally diverse chemicals in fish using artificial intelligence approaches.
Singh KP; Gupta S; Rai P
Ecotoxicol Environ Saf; 2013 Sep; 95():221-33. PubMed ID: 23764236
[TBL] [Abstract][Full Text] [Related]
10. Prediction of the acute toxicity (96-h LC50) of organic compounds to the fathead minnow (Pimephales promelas) using a group contribution method.
Martin TM; Young DM
Chem Res Toxicol; 2001 Oct; 14(10):1378-85. PubMed ID: 11599929
[TBL] [Abstract][Full Text] [Related]
11. Tuning neural and fuzzy-neural networks for toxicity modeling.
Mazzatorta P; Benfenati E; Neagu CD; Gini G
J Chem Inf Comput Sci; 2003; 43(2):513-8. PubMed ID: 12653515
[TBL] [Abstract][Full Text] [Related]
12. A similarity-based QSAR model for predicting acute toxicity towards the fathead minnow (Pimephales promelas).
Cassotti M; Ballabio D; Todeschini R; Consonni V
SAR QSAR Environ Res; 2015; 26(3):217-43. PubMed ID: 25780951
[TBL] [Abstract][Full Text] [Related]
13. Prediction of acute toxicity in fish by using QSAR methods and chemical modes of action.
Lozano S; Lescot E; Halm MP; Lepailleur A; Bureau R; Rault S
J Enzyme Inhib Med Chem; 2010 Apr; 25(2):195-203. PubMed ID: 19874208
[TBL] [Abstract][Full Text] [Related]
14. Robust modelling of acute toxicity towards fathead minnow (Pimephales promelas) using counter-propagation artificial neural networks and genetic algorithm.
Drgan V; Župerl Š; Vračko M; Como F; Novič M
SAR QSAR Environ Res; 2016 Jul; 27(7):501-19. PubMed ID: 27322761
[TBL] [Abstract][Full Text] [Related]
15. A QSAR for baseline toxicity: validation, domain of application, and prediction.
Oberg T
Chem Res Toxicol; 2004 Dec; 17(12):1630-7. PubMed ID: 15606139
[TBL] [Abstract][Full Text] [Related]
16. QSAR modelling of the ERL-D fathead minnow acute toxicity database.
Nendza M; Russom CL
Xenobiotica; 1991 Feb; 21(2):147-70. PubMed ID: 2058173
[TBL] [Abstract][Full Text] [Related]
17. CORAL: QSAR models for acute toxicity in fathead minnow (Pimephales promelas).
Toropova AP; Toropov AA; Lombardo A; Roncaglioni A; Benfenati E; Gini G
J Comput Chem; 2012 May; 33(12):1218-23. PubMed ID: 22371019
[TBL] [Abstract][Full Text] [Related]
18. A new strategy for using supervised artificial neural networks in QSAR.
Devillers J
SAR QSAR Environ Res; 2005 Oct; 16(5):433-42. PubMed ID: 16272042
[TBL] [Abstract][Full Text] [Related]
19. QSAR study of the acute toxicity to fathead minnow based on a large dataset.
Wu X; Zhang Q; Hu J
SAR QSAR Environ Res; 2016; 27(2):147-64. PubMed ID: 26911563
[TBL] [Abstract][Full Text] [Related]
20. Toxicity of organic chemicals to fathead minnow: a united quantitative structure-activity relationship model and its application.
Feng L; Han S; Zhao Y; Wang L; Chen J
Chem Res Toxicol; 1996; 9(3):610-3. PubMed ID: 8728506
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]