Prediction of Drug Lipophilicity using Back Propagation Artificial Neural Network Modeling
نویسندگان
چکیده
منابع مشابه
Prediction of Drug Lipophilicity Using Back Propagation Artificial Neural Network Modeling
A quantitative structure–property relationship (QSPR) study was performed to develop models those relate the structures of 150 drug organic compounds to their n-octanol–water partition coefficients (logPo/w). Molecular descriptors derived solely from 3D structures of the molecular drugs. A genetic algorithm was also applied as a variable selection tools in QSPR analysis. The models were constru...
متن کاملscour modeling piles of kambuzia industrial city bridge using hec-ras and artificial neural network
today, scouring is one of the important topics in the river and coastal engineering so that the most destruction in the bridges is occurred due to this phenomenon. whereas the bridges are assumed as the most important connecting structures in the communications roads in the country and their importance is doubled while floodwater, thus exact design and maintenance thereof is very crucial. f...
Assembly Quality Prediction Based on Back- propagation Artificial Neural Network
Because of the severe geometrical distortion induced by the optical system and the limited kinetic accuracy of mechanical system in the vision-based mobile-phone lens’s assembly system, the nonlinear, perspective distortion errors and the kinematics errors generally exist in the assembly process of the mobile-phone lens. It is necessary to predict the assembly quality of the vision-based mobile...
متن کاملPrediction of ultimate strength of shale using artificial neural network
A rock failure criterion is very important for prediction of the ultimate strength in rock mechanics and geotechnics; it is determined for rock mechanics studies in mining, civil, and oil wellborn drilling operations. Also shales are among the most difficult to treat formations. Therefore, in this research work, using the artificial neural network (ANN), a model was built to predict the ultimat...
متن کاملPrediction of Mechanical Properties of TWIP Steels using Artificial Neural Network Modeling
In recent years, great attention has been paid to the development of high manganese austenitic TWIP steels exhibiting high tensile strength and exceptional total elongation. Due to low stacking fault energy (SFE), cross slip becomes more difficult in these steels and mechanical twinning is then the favored deformation mode besides dislocation gliding. Chemical composition along with processing ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Oriental Journal of Chemistry
سال: 2014
ISSN: 0970-020X,2231-5039
DOI: 10.13005/ojc/300253