DocumentCode
3782784
Title
Artificial neural network applications in immunology
Author
V. Brusic;J. Zeleznikow
Author_Institution
Kent Ridge Digital Labs., Singapore
Volume
5
fYear
1999
Firstpage
3685
Abstract
Artificial neural network (ANN) applications in immunology include simulations of peptide binding to histocompatibility complex molecules, which present peptides for recognition by the immune system. These peptides are derived from protein antigens and represent prime targets for vaccine discovery. ANN models have proven superior when compared to the alternative models. Applications of ANN models help minimise the number of necessary wet-lab experiments. In this article we describe three specific applications in which targets of immune recognition have been determined from diabetes-, melanoma-, and malaria-related antigens.
Keywords
"Artificial neural networks","Intelligent networks","Immune system","Peptides","Hidden Markov models","Amino acids","Computational modeling","Proteins","Vaccines","Target recognition"
Publisher
ieee
Conference_Titel
Neural Networks, 1999. IJCNN ´99. International Joint Conference on
ISSN
1098-7576
Print_ISBN
0-7803-5529-6
Type
conf
DOI
10.1109/IJCNN.1999.836269
Filename
836269
Link To Document