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Glycobiology of immune responses

Open access
Rabinovich, Gabriel A., van Kooyk, Yvette, Cobb, Brian A.·2012·Annals of the New York Academy of Sciences

Abstract

Unlike their protein “roommates” and their nucleic acid “cousins," carbohydrates remain an enigmatic arm of biology. The central reason for the difficulty in fully understanding how carbohydrate structure and biological function are tied is the nontemplate nature of their synthesis and the resulting heterogeneity. The goal of this collection of expert reviews is to highlight what is known about how carbohydrates and their binding partners—the microbial (non‐self), tumor (altered‐self), and host (self)—cooperate within the immune system, while also identifying areas of opportunity to those willing to take up the challenge of understanding more about how carbohydrates influence immune responses. In the end, these reviews will serve as specific examples of how carbohydrates are as integral to biology as are proteins, nucleic acids, and lipids. Here, we attempt to summarize general concepts on glycans and glycan‐binding proteins (mainly C‐type lectins, siglecs, and galectins) and their contributions to the biology of immune responses in physiologic and pathologic settings.

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Metadata

Authors
Rabinovich, G. A., van Kooyk, Y., & Cobb, B. A.
Venue
Annals of the New York Academy of Sciences
Publisher
Wiley
Published
2012-04
Volume
1253
Issue
1
Pages
1-15
ISSN
  • 0077-8923 (ISSN-L)
  • 1749-6632
OpenAlex
W2142574184
Cited by
279
References
14
FWCI
7.67
Type
journal article
Language
en
Open access
bronze

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CoChat. (2026). Citation check: Glycobiology of immune responses. https://app.cochat.ai/papers/10.1111/j.1749-6632.2012.06492.x
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Rabinovich, G. A., van Kooyk, Y., & Cobb, B. A. (2012). Glycobiology of immune responses. Annals of the New York Academy of Sciences. https://doi.org/10.1111/j.1749-6632.2012.06492.x

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.