TY  - UNPB
T2  - European Symposium on Computer Aided Process Engineering, ESCAPE14
KW  - Radial Basis Functions
KW  -  QSAR
KW  -  Neural Networks
KW  -  Evolutionary Computing
KW  -  Genetic Algorithms
KW  -  Simulating Annealing
UR  - http://www.deb.uminho.pt/escape14/PDFs/PPDp011.pdf
A1  - Patrinos, Panagiotis
A1  - Alexandridis, Alex
A1  - Afantitis, Antreas
A1  - Sarimveis, Haralambos
A1  - Igglesi-Markopoulou, Olga
Y1  - 2004///
ID  - eprints1039
TI  - Development of nonlinear quantitative structure-activity relationships using RBF networks and evolutionary computing
N2  - Quantitative Structure Activity Relationships (QSARs) are mathematical models that correlate structural or property descriptions of compounds (hydrophobicity, topology, electronic properties etc.) with activities, such as chemical measurements and biological assays. In this paper we propose a modeling methodology suitable for QSAR studies which selects the proper descriptors based on evolutionary computing and finally produces Radial Basis Function (RBF) neural network models. The method is successfully applied to the benchmark Selwood data set.
AV  - none
M2  - Lisbon, Portugal
ER  -