Computational immunology: The coming of age.
The explosive growth in biotechnology combined with major advances in information technology has the potential to radically transform immunology in the postgenomics era. Not only do we now have ready access to vast quantities of existing data, but new data with relevance to immunology are being accumulated at an exponential rate. Resources for computational immunology include biological databases and methods for data extraction, comparison, analysis and interpretation. Publicly accessible biological databases of relevance to immunologists number in the hundreds and are growing daily. The ability to efficiently extract and analyse information from these databases is vital for efficient immunology research. Most importantly, a new generation of computational immunology tools enables modelling of peptide transport by the transporter associated with antigen processing (TAP), modelling of antibody binding sites, identification of allergenic motifs and modelling of T-cell receptor serial triggering.
Petrovsky
Nikolai
N
National BioinformaticsCentre, University of Canberra and National Health Sciences Centre,Canberra Clinical School, Woden, Australian Capital Territory, Australia. nikolai.petrovsky@anu.edu.au
Brusic
Vladimir
V
D000941:Antigens / Q000737:chemistry; D019295:Computational Biology; D003658:Decision Making, Computer-Assisted; D004198:Disease Susceptibility / Q000276:immunology; D018984:Epitopes, T-Lymphocyte / Q000737:chemistry / Q000235:genetics; D005544:Forecasting / Q000379:methods; D006680:HLA Antigens / Q000737:chemistry / Q000235:genetics; D006801:Humans; D007111:Immunity, Cellular / Q000235:genetics; D007158:Immunologic Techniques; D016247:Information Storage and Retrieval; D016377:Organ Transplantation / Q000534:rehabilitation; D014181:Transplantation Immunology / Q000502:physiology
D000941:Antigens; D018984:Epitopes, T-Lymphocyte; D006680:HLA Antigens