The astounding diversity of immune system components (e.g. immunoglobulins, lymphocyte receptors, or cytokines) together with the complexity of the regulatory pathways and network-type interactions makes immunology a combinatorial science. Currently available data represent only a tiny fraction of possible situations and data continues to accrue at an exponential rate. Computational analysis has therefore become an essential element of immunology research with a main role of immunoinformatics being the management and analysis of immunological data. More advanced analyses of the immune system using computational models typically involve conversion of an immunological question to a computational problem, followed by solving of the computational problem and translation of these results into biologically meaningful answers. Major immunoinformatics developments include immunological databases, sequence analysis, structure modelling, mathematical modelling of the immune system, simulation of laboratory experiments, statistical support for immunological experimentation and immunogenomics. In this paper we describe the status and challenges within these sub-fields. We foresee the emergence of immunomics not only as a collective endeavour by researchers to decipher the sequences of T cell receptors, immunoglobulins, and other immune receptors, but also to functionally annotate the capacity of the immune system to interact with the whole array of self and non-self entities, including genome-to-genome interactions.
|Number of pages||11|
|Journal||Novartis Foundation Symposium|
|Publication status||Published - 1 Dec 2003|