219 related articles for article (PubMed ID: 25694078)
1. Mutagenicity: QSAR - quasi-QSAR - nano-QSAR.
Toropova AP; Toropov AA
Mini Rev Med Chem; 2015; 15(8):608-21. PubMed ID: 25694078
[TBL] [Abstract][Full Text] [Related]
2. Quasi-QSAR for mutagenic potential of multi-walled carbon-nanotubes.
Toropov AA; Toropova AP
Chemosphere; 2015 Apr; 124():40-6. PubMed ID: 25465947
[TBL] [Abstract][Full Text] [Related]
3. Nano-QSAR: Model of mutagenicity of fullerene as a mathematical function of different conditions.
Toropova AP; Toropov AA; Veselinović AM; Veselinović JB; Benfenati E; Leszczynska D; Leszczynski J
Ecotoxicol Environ Saf; 2016 Feb; 124():32-36. PubMed ID: 26452192
[TBL] [Abstract][Full Text] [Related]
4. Quasi-SMILES and nano-QFAR: united model for mutagenicity of fullerene and MWCNT under different conditions.
Toropov AA; Toropova AP
Chemosphere; 2015 Nov; 139():18-22. PubMed ID: 26026259
[TBL] [Abstract][Full Text] [Related]
5. Quasi-SMILES-Based Nano-Quantitative Structure-Activity Relationship Model to Predict the Cytotoxicity of Multiwalled Carbon Nanotubes to Human Lung Cells.
Trinh TX; Choi JS; Jeon H; Byun HG; Yoon TH; Kim J
Chem Res Toxicol; 2018 Mar; 31(3):183-190. PubMed ID: 29439565
[TBL] [Abstract][Full Text] [Related]
6. Optimal descriptor as a translator of eclectic data into endpoint prediction: mutagenicity of fullerene as a mathematical function of conditions.
Toropov AA; Toropova AP
Chemosphere; 2014 Jun; 104():262-4. PubMed ID: 24246220
[TBL] [Abstract][Full Text] [Related]
7. Mutagenicity, anticancer activity and blood brain barrier: similarity and dissimilarity of molecular alerts.
Toropov AA; Toropova AP; Benfenati E; Salmona M
Toxicol Mech Methods; 2018 Jun; 28(5):321-327. PubMed ID: 29281931
[TBL] [Abstract][Full Text] [Related]
8. CORAL and Nano-QFAR: Quantitative feature - Activity relationships (QFAR) for bioavailability of nanoparticles (ZnO, CuO, Co
Toropova AP; Toropov AA; Leszczynska D; Leszczynski J
Ecotoxicol Environ Saf; 2017 May; 139():404-407. PubMed ID: 28192776
[TBL] [Abstract][Full Text] [Related]
9. Nano-QSAR in cell biology: Model of cell viability as a mathematical function of available eclectic data.
Toropova AP; Toropov AA
J Theor Biol; 2017 Mar; 416():113-118. PubMed ID: 28087422
[TBL] [Abstract][Full Text] [Related]
10. QSAR modelling for mutagenic potency of heteroaromatic amines by optimal SMILES-based descriptors.
Toropov AA; Toropova AP; Benfenati E
Chem Biol Drug Des; 2009 Mar; 73(3):301-12. PubMed ID: 19207466
[TBL] [Abstract][Full Text] [Related]
11. Use of the index of ideality of correlation to improve predictive potential for biochemical endpoints.
Toropov AA; Toropova AP
Toxicol Mech Methods; 2019 Jan; 29(1):43-52. PubMed ID: 30064284
[TBL] [Abstract][Full Text] [Related]
12. Prediction of the adsorption coefficients of some aromatic compounds on multi-wall carbon nanotubes by the Monte Carlo method.
Ahmadi S; Akbari A
SAR QSAR Environ Res; 2018 Nov; 29(11):895-909. PubMed ID: 30332923
[TBL] [Abstract][Full Text] [Related]
13. 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]
14. coral Software: QSAR for Anticancer Agents.
Benfenati E; Toropov AA; Toropova AP; Manganaro A; Gonella Diaza R
Chem Biol Drug Des; 2011 Jun; 77(6):471-6. PubMed ID: 21435183
[TBL] [Abstract][Full Text] [Related]
15. Application of QSARs in identification of mutagenicity mechanisms of nitro and amino aromatic compounds against Salmonella typhimurium species.
Jillella GK; Khan K; Roy K
Toxicol In Vitro; 2020 Jun; 65():104768. PubMed ID: 31926304
[TBL] [Abstract][Full Text] [Related]
16. Prediction of aromatic amines mutagenicity from theoretical molecular descriptors.
Gramatica P; Consonni V; Pavan M
SAR QSAR Environ Res; 2003 Aug; 14(4):237-50. PubMed ID: 14506868
[TBL] [Abstract][Full Text] [Related]
17. 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]
18. Quasi-SMILES: quantitative structure-activity relationships to predict anticancer activity.
Toropova AP; Toropov AA
Mol Divers; 2019 May; 23(2):403-412. PubMed ID: 30306392
[TBL] [Abstract][Full Text] [Related]
19. CORAL: Binary classifications (active/inactive) for drug-induced liver injury.
Toropova AP; Toropov AA
Toxicol Lett; 2017 Feb; 268():51-57. PubMed ID: 28111161
[TBL] [Abstract][Full Text] [Related]
20. QSAR as a random event: modeling of nanoparticles uptake in PaCa2 cancer cells.
Toropov AA; Toropova AP; Puzyn T; Benfenati E; Gini G; Leszczynska D; Leszczynski J
Chemosphere; 2013 Jun; 92(1):31-7. PubMed ID: 23566368
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
