چکیده مقاله
In this work, the cellular uptake of 109 magneto nanoparticles MNPs in human pancreatic cancer cells Paca2 were predicted by applying quantitative nanostructureactivityrelationship QNAR methodology The most important descriptors selected by stepwise multiple linear regression SW MLR Some feature mapping techniques such asrandom forest RF , multiple linear regression MLR and least square support vector machine LS SVM were used for development of QNAR model Inspection to these models indicates LS SVM model is finely capable for predicting the cellular uptake of MNPs For this model, the correlation coefficient R was 0 935 and 0 933, and the root mean square error RMSE was 0 16 and 0 23 for the training and test sets, respectively The built LSSVM model was assessed by leave one out cross validation Q2= 0 53, SPRESS=0 16 as well as external validation In addition, sensitivity analysis of LS SVM model indicated the role of electronic and steric interactions of MNPʼs organic coating are the predominant factors responsible for cellular uptake in Paca2
کلیدواژهها
نویسندگان
Zahra Pahlavan Yali
Mohammad Hossein Fatemi
Mohammad Hossein Fatemi
Zahra Pahlavan Yali
شیوه ارجاع
Pahlavan Yali, Zahra and Fatemi, Mohammad Hossein,1396,Application of some feature mapping methods in QNAR prediction of cellular uptake of magneto fluorescent nanoparticles,2rd International Conference on Soft Computing,Rudsar
ارائهشده در
مجموعه مقالات دومین کنفرانس ملی محاسبات نرم1 آذر 1396 · رودسر