Year: 2022
Type: book-chapter
Abstract: Adaptive immune receptor repertoires (AIRRs) are rich with information that can be mined for insights into the workings of the immune system. Gene usage, CDR3 properties, clonal lineage structure, and sequence diversity are all capable of revealing the dynamic immune response to perturbation by disease, vaccination, or other interventions. Here we focus on a conceptual introduction to the many aspects of repertoire analysis and orient the reader toward the uses and advantages of each. Along the way, we note some of the many software tools that have been developed for these investigations and link the ideas discussed to chapters on methods provided elsewhere in this volume.
Source: Methods in molecular biology
Authors: Susanna Marquez, Lmar Babrak, Victor Greiff, Kenneth B. Hoehn, William D. Lees, Eline T. Luning Prak, Enkelejda Miho, Aaron M. Rosenfeld, Chaim A. Schramm, Ulrik Stervbo, on behalf of the AIRR Community
Institutions: Yale University, FHNW University of Applied Sciences and Arts Northwestern Switzerland, Oslo University Hospital, University of Oslo, University of London, Institute of Structural and Molecular Biology, Birkbeck, University of London, University of Pennsylvania, SIB Swiss Institute of Bioinformatics, National Institutes of Health, National Institute of Allergy and Infectious Diseases, Vaccine Research Center, University Hospitals of the Ruhr-University of Bochum, Universitätsklinik Marien Hospital Herne
Language: English
Topic: T-cell and B-cell Immunology
Subfield: Immunology
Field: Immunology and Microbiology
Domain: Life Sciences
Open Access status: hybrid
Awards: Verbund e:Kid - Teilprojekt Charite, Immunologische und genetische Analyse um die Pathogenese von primärer selektiver IgMImmundefizienz (sIgMID) zu verstehen, University of Pennsylvania Clinical Autoimmunity Center of Excellence, Verbundprojekt: Frühdetektion von Schmerzchronifizierung (NoChro) - Teilvorhaben: Erforschung löslicher Faktoren für die Frühdetektion der Chronifizierung, Discovery of anti-DENV Antibodies Using Artificial Intelligence, G8158204233
OpenAlex ID: W4285132606