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Computational models in immunological methods: an historical review

S J Merrill1

  • 1Department of Mathematics, Statistics and Computer Science, Marquette University, Milwaukee, WI 53201-1881, USA.

Journal of Immunological Methods
|October 6, 1998
PubMed
Summary
This summary is machine-generated.

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Computational models have been integral to immunology since its inception, aiding in understanding processes like antibody-antigen binding. This review traces their historical use in immunological assays and methods.

Area of Science:

  • Immunology
  • Computational Biology
  • Bioinformatics

Background:

  • Computational models have been foundational in immunology since its origins.
  • They are crucial for integrating theoretical understanding with experimental data.

Observation:

  • This review examines the historical role of computational models in immunology laboratories.
  • It analyzes papers from the Journal of Immunological Methods (Volumes 1-208) focusing on new models and instrument enhancements.
  • Mathematical descriptions of fundamental immunological assays are provided.

Findings:

  • Computational models, including mathematical, statistical, and computer simulations, have evolved significantly.
  • Key papers introducing novel modeling approaches and instrument improvements are cited and categorized by model type.

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Implications:

  • Understanding the historical trajectory of computational modeling provides context for current immunological research.
  • This review highlights the enduring importance of computational approaches in advancing immunological knowledge and laboratory techniques.