Artificial neural network applications in immunology

Vladimir Brusic, John Zeleznikow

Research output: Contribution to conferencePaper

4 Citations (Scopus)

Abstract

Artificial neural network (ANN) applications in immunology include simulations of peptide binding to MHC 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 minimize 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.

Original languageEnglish
Pages3685-3689
Number of pages5
Publication statusPublished - Dec 1 1999
EventInternational Joint Conference on Neural Networks (IJCNN'99) - Washington, DC, USA
Duration: Jul 10 1999Jul 16 1999

Other

OtherInternational Joint Conference on Neural Networks (IJCNN'99)
CityWashington, DC, USA
Period7/10/997/16/99

ASJC Scopus subject areas

  • Software
  • Artificial Intelligence

Fingerprint Dive into the research topics of 'Artificial neural network applications in immunology'. Together they form a unique fingerprint.

  • Cite this

    Brusic, V., & Zeleznikow, J. (1999). Artificial neural network applications in immunology. 3685-3689. Paper presented at International Joint Conference on Neural Networks (IJCNN'99), Washington, DC, USA, .