Prediction of the effect of formulation on the toxicity of chemicals
| Autor: | Mistry, Pritesh, Neagu, Daniel, Sanchez-Ruiz, A., Trundle, Paul R., Vessey, J.D., Gosling, J.P. |
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| Jazyk: | angličtina |
| Rok vydání: | 2017 |
| Předmět: | |
| Druh dokumentu: | Článek |
| DOI: | 10.1039/C6TX00303F |
| Popis: | Yes Two approaches for the prediction of which of two vehicles will result in lower toxicity for anticancer agents are presented. Machine-learning models are developed using decision tree, random forest and partial least squares methodologies and statistical evidence is presented to demonstrate that they represent valid models. Separately, a clustering method is presented that allows the ordering of vehicles by the toxicity they show for chemically-related compounds. |
| Databáze: | Networked Digital Library of Theses & Dissertations |
| Externí odkaz: |
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