AbstractThe utilization of computational models in immunology dates from the birth of the science. From the description of antibody-antigen binding to the structural models of receptors, models are utilized to bring fundamental understandings of the processes together with laboratory measurements to uncover implications of these data.
In this review, an historical view of the role of computational models in the immunology laboratory is presented, and short mathematical descriptions are given of fundamental assays. In addition, the range of current uses of models is explored -- especially as seen through papers which have appeared in the Journal of Immunological Methods from Volume 1 (1971/2) to Volume 208 (1997). Each paper which introduced a new mathematical, statistical, or computer simulation model, or introduced an enhancement to an instrument through a model in those volumes is cited and the type of computational model noted.
Keywords: immunological methods, statistics, simulation, computer model, mathematical model, software, immunological assays
Contents
1. Introduction
2. Historical Examples
complement fixation
the precipitin reaction
3. Modern contributions
qualtity (affinity) of antibody
agglutination and hemagglutination
immunoassays - quantification of antibody or ligands
the Farr assay
radioimmunoassays
precipitation reaction in gels
nephelometry
immunofluorescence and fluorescent labeling of cells
enzyme immunoassay and ELISA
cellular assays
cytotoxicity assays
migration, migration inhibition, phagocytosis assays
limiting dilution assays
basophil degranulation
proliferation assays
miscellaneous assays
other general topics
computational approaches to data and design
gene sequencing and libraries
structures of proteins
pcr - the polymerase chain reaction
image enhancement
Acknowledgements
References
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