Data cleansing for computer models: A case study from immunology

Vladirnir Brusic, John Zeleznikow, Tiziana Sturniolo, Elisa Bono, Jürgen Hammer

Research output: Chapter in Book/Report/Conference proceedingConference contribution

8 Citations (Scopus)

Abstract

Knowledge discovery from databases (KDD) in biology largely depends on the use of accurate computer models of biological processes. KDD applications in immunology include the discovery of vaccine targets and new functional relations within the immune system. We describe a process of development and refinement of artificial neural network models of the human HLA-DR1 molecule, useful for the discovery of peptide vaccines. High accuracy of these models was achieved by data cleansing techniques and by cyclical retraining using new data.

Original languageEnglish
Title of host publicationICONIP 1999, 6th International Conference on Neural Information Processing - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages603-609
Number of pages7
ISBN (Electronic)0780358716, 9780780358713
DOIs
Publication statusPublished - 1999
Externally publishedYes
Event6th International Conference on Neural Information Processing, ICONIP 1999 - Perth, Australia
Duration: Nov 16 1999Nov 20 1999

Publication series

NameICONIP 1999, 6th International Conference on Neural Information Processing - Proceedings
Volume2

Conference

Conference6th International Conference on Neural Information Processing, ICONIP 1999
CountryAustralia
CityPerth
Period11/16/9911/20/99

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computational Theory and Mathematics
  • Computer Networks and Communications
  • Statistics, Probability and Uncertainty

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