Bioinformatics for study of autoimmunity

Nikolai Petrovsky, Vladimir Brusic

Research output: Contribution to journalArticle

14 Citations (Scopus)

Abstract

Recent years have witnessed an explosive growth in available biological data pertaining to autoimmunity research. This includes a tremendous quantity of sequence data (biological structures, genetic and physical maps, pathways, etc.) generated by genome and proteome projects plus extensive clinical and epidemiological data. Autoimmunity research stands to greatly benefit from this data so long as appropriate strategies are available to enable full access to and utilization of this data. The quantity and complexity of this biological data necessitates use of advanced bioinformatics strategies for its efficient retrieval, analysis and interpretation. Major progress has been made in development of specialized tools for storage, analysis and modeling of immunological data, and this has led to development of a whole new field know as immunoinformatics. With advances in novel high-throughput immunology technologies immunoinformatics is transforming understanding of how the immune system functions. This paper reviews advances in the field of immunoinformatics pertinent to autoimmunity research including databases, tools in genomics and proteomics, tools for study of B- and T-cell epitopes, integrative approaches, and web servers.

Original languageEnglish
Pages (from-to)635-643
Number of pages9
JournalAutoimmunity
Volume39
Issue number8
DOIs
Publication statusPublished - Dec 1 2006

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Keywords

  • Computational immunology
  • Databases
  • Immunoinformatics
  • Predictive models

ASJC Scopus subject areas

  • Immunology and Allergy
  • Immunology

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