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A neural network based prediction of octanol–water partition coefficients using atomic5 fragmental descriptors

✍ Scribed by László Molnár; György M. Keserű; Ákos Papp; Zsolt Gulyás; Ferenc Darvas


Book ID
108073190
Publisher
Elsevier Science
Year
2004
Tongue
English
Weight
215 KB
Volume
14
Category
Article
ISSN
0960-894X

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Prediction of octanol–water partition co
✍ Hassan Golmohammadi 📂 Article 📅 2009 🏛 John Wiley and Sons 🌐 English ⚖ 206 KB 👁 1 views

## Abstract A quantitative structure–property relationship (QSPR) study was performed to develop models those relate the structure of 141 organic compounds to their octanol–water partition coefficients (log __P__~o/w~). A genetic algorithm was applied as a variable selection tool. Modeling of log _