شماره ركورد كنفرانس :
1771
عنوان مقاله :
Prediction EC50 some compounds by Multi linear regression (MLR) and partial linear regression (PLS)
پديدآورندگان :
Fatemi Mohammad Hossein نويسنده Chemometrics Laboratory, Faculty of Chemistry, University of Mazandaran, Babolsar, Iran , Shakeri Panteha نويسنده , Baher Elham نويسنده
كليدواژه :
Quantitative structure–activity relationship (QSAR) , Multiple Linear Regression (MLR)
عنوان كنفرانس :
The First Conference and Workshop on Mathematical Chemistry
چكيده فارسي :
Quantitative structure–activity relationship (QSAR) analysis has been directed to a series of
substituted aromatic compounds. Modeling of the 50% effective inhibition concentration (48
h – EC50) as a function of the theoretically derived descriptors was established by multiple
linear regression (MLR) and partial least squares (PLS) regression. Appropriate models with
low standard errors and high correlation was used. A comparison of the two regression
methods used showed that MLR has a better prediction ability than PLS.
شماره مدرك كنفرانس :
1758929
