| scholarly article | Q13442814 |
| P356 | DOI | 10.1016/S1383-5718(00)00167-4 |
| P698 | PubMed publication ID | 11287295 |
| P2093 | author name string | G G Cash | |
| P2860 | cites work | SMILES, a chemical language and information system. 1. Introduction to methodology and encoding rules | Q28090714 |
| Mutagenicity studies of benzidine and its analogs: structure-activity relationships | Q28141773 | ||
| Quantitative structure-activity (QSAR) relationships of mutagenic aromatic and heterocyclic amines | Q38463978 | ||
| Review of mutagenicity of monocyclic aromatic amines: quantitative structure-activity relationships | Q41560466 | ||
| Quantitative structure-activity relationships of mutagenic aromatic and heteroaromatic azides and amines | Q43496671 | ||
| A QSAR investigation of the role of hydrophobicity in regulating mutagenicity in the Ames test: 1. Mutagenicity of aromatic and heteroaromatic amines in Salmonella typhimurium TA98 and TA100. | Q44104976 | ||
| QSAR models for both mutagenic potency and activity: application to nitroarenes and aromatic amines. | Q50154407 | ||
| Predicting mutagenicity of chemicals using topological and quantum chemical parameters: a similarity based study | Q72049100 | ||
| QSAR models for discriminating between mutagenic and nonmutagenic aromatic and heteroaromatic amines | Q77102158 | ||
| P433 | issue | 1-2 | |
| P407 | language of work or name | English | Q1860 |
| P921 | main subject | genotoxicity | Q1009245 |
| P304 | page(s) | 31-37 | |
| P577 | publication date | 2001-04-01 | |
| P1433 | published in | Mutation Research | Q6943732 |
| P1476 | title | Prediction of the genotoxicity of aromatic and heteroaromatic amines using electrotopological state indices | |
| P478 | volume | 491 |
| Q44484209 | Improved in silico prediction of carcinogenic potency (TD50) and the risk specific dose (RSD) adjusted Threshold of Toxicological Concern (TTC) for genotoxic chemicals and pharmaceutical impurities |
| Q50086183 | In silico screening of chemicals for bacterial mutagenicity using electrotopological E-state indices and MDL QSAR software. |
| Q40548909 | Predicting the carcinogenic potential of pharmaceuticals in rodents using molecular structural similarity and E-state indices |
| Q50079354 | Prediction of genotoxicity of various environmental pollutants by artificial neural network simulation. |
| Q48048668 | QSAR modeling for predicting mutagenic toxicity of diverse chemicals for regulatory purposes |
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