Title :
Discrimination analysis of structure-toxicity relationships on silatranes by artificial neural network
Author_Institution :
Res. Center of Technol., Acad. Sinica, Shanghai, China
fDate :
27 Jun-2 Jul 1994
Abstract :
The structure-toxicity relationships of silatranes was studied by using backpropagation model which is one of the typical artificial neural networks. A group of samples were collected as an object of study. The results of chemical experiment and toxic detection showed that the successful rate reached 100%. Therefore the performance of the neural network approach is good, and it might be referred as an effective assistant technique for analysis of structure-activity relationships of medicine
Keywords :
backpropagation; medical computing; neural nets; pattern recognition; artificial neural network; backpropagation model; discrimination analysis; silatranes; structure-activity relationships; structure-toxicity relationships; toxic detection; Artificial neural networks; Chemical compounds; Chemical technology; Cities and towns; Computer aided instruction; Hair; Network synthesis; Neural networks; Proteins; Toxic chemicals;
Conference_Titel :
Neural Networks, 1994. IEEE World Congress on Computational Intelligence., 1994 IEEE International Conference on
Conference_Location :
Orlando, FL
Print_ISBN :
0-7803-1901-X
DOI :
10.1109/ICNN.1994.374731
