Zobrazeno 1 - 4
of 4
pro vyhledávání: '"Rokaya Mouhibi"'
Publikováno v:
Open Journal of Medicinal Chemistry. :7-15
Quantitative structure–activity relationship (QSAR) models were developed to predict for CCR5 binding affinity of substituted 1-(3, 3-diphenylpropyl)-piperidinyl amides and ureas using multiple linear regression (MLR) and artificial neural network
Publikováno v:
Open Journal of Medicinal Chemistry. :100-120
A series of N-carbonyl-functionalized ureas, carbamates and thiocarbamates derivatives (or N-Chloro sulfonyl isocyanate “N-CSI”) were involved in linear and nonlinear physicochemical quantitative structure-activity relationship “QSAR” analysi
Publikováno v:
International Journal of Bioinformatics Research and Applications. 12:116
Quantitative Structure Activity Relationships QSAR were studied for a series of 54 1-3, 3-diphenylpropyl-piperidinyl amides and ureas derivatives by means of Multiple Linear Regression MLR, Genetic Algorithm GA and Artificial Neural Network ANN techn
Autor:
Mohamed Lazar, M. Abdellah Bahlaoui, Mohamed Nohair, Rokaya Mouhibi, Marouan Bnoumarzouk, Mohamed Zahouily
Publikováno v:
Chemical Product and Process Modeling. 3
Structure-activity relationships were studied for a series of 46 2.6-dimethyl-3.5-dicabomethoxy-4-phenyl-1.4-dihydropyridine derivatives by means of multiple linear regression (MLR) and artificial neural network (ANN) techniques. The values of log (1