Title :
Quantitative structure-activity relationships of Benzodiazepines by recursive cascade correlation
Author :
Bianucci, Anna Maria ; Micheli, Alessio ; Sperduti, Alessandro ; Starita, Antonina
Author_Institution :
Dipt. di Sci. Farmaceutiche, Pisa Univ., Italy
Abstract :
An application of recursive cascade correlation to the quantitative structure-activity relationships (QSAR) of a class of Beneodiazepines is presented. Recursive cascade correlation is a neural network model recently proposed for the processing of structured data. This allows the direct treatment of the chemical compounds as labeled ordered trees, which constitutes a novel approach to QSAR. Our approach compares favorably versus the traditional QSAR treatment based on equations
Keywords :
chemistry computing; correlation methods; learning (artificial intelligence); medical computing; neural nets; pattern classification; trees (mathematics); Beneodiazepines; acyclic graphs; biological response; chemical compounds; drug; labelled directed trees; learning; molecular structure representation; pattern classification; quantitative structure-activity relationships; recursive cascade correlation; recursive neural networks; Biological information theory; Biological system modeling; Chemical compounds; Differential equations; Drugs; Feedforward neural networks; Helium; Neural networks; Relays; Systematics;
Conference_Titel :
Neural Networks Proceedings, 1998. IEEE World Congress on Computational Intelligence. The 1998 IEEE International Joint Conference on
Conference_Location :
Anchorage, AK
Print_ISBN :
0-7803-4859-1
DOI :
10.1109/IJCNN.1998.682247
