Immunology for physicists
Abstract
The immune system is a complex system of cells and molecules that can provide us with a basic defense against pathogenic organisms. Like the nervous system, the immune system performs pattern recognition tasks, learns, and retains a memory of the antigens that it has fought. The immune system contains more than ${10}^{7}$ different clones of cells that communicate via cell-cell contact and the secretion of molecules. Performing complex tasks such as learning and memory involves cooperation among large numbers of components of the immune system and hence there is interest in using methods and concepts from statistical physics. Furthermore, the immune response develops in time and the description of its time evolution is an interesting problem in dynamical systems. In this paper, the authors provide a brief introduction to the biology of the immune system and discuss a number of immunological problems in which the use of physical concepts and mathematical methods has increased our understanding.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The basic McCulloch-Pitts design is common to many other living systems, including gene regulatory networks, immune networks, collective intelligence or some aneural systems, such as quorum-sensing decisions in microbial communities.
“Interestingly, the basic McCulloch–Pitts design is common to many other living systems, including gene regulatory networks [256–259], immune networks [260–262], collective intelligence [263–267] or some aneural systems, such as quorum-sensing decisions in microbial communities, where an explicit equivalence has been defined [268].”
From Fundamental constraints to the logic of living systems (2024) · cites this paper as [261]
Cites
A simple model for the immune network.
Parisi, G. (1990) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.87.1.429 · Cited by 104 · see citing works
Adaptive Dynamic Networks as Models for the Immune System and Autocatalytic Sets
FARMER, J. D., KAUFFMAN, S. A., PACKARD, N. H., & PERELSON, A. S. (1987) · Annals of the New York Academy of Sciences · doi:10.1111/j.1749-6632.1987.tb48728.x · Cited by 59 · see citing works
Self-citation
Flagged first, then by citations
Cited by
Sorted by citations
Understanding the human antibody repertoire
Rees, A. R. (2020) · mAbs · doi:10.1080/19420862.2020.1729683 · Cited by 108 · see citing works
Cancer-driven dynamics of immune cells in a microfluidic environment
Agliari, E., Biselli, E., De Ninno, A., Schiavoni, G., Gabriele, L., Gerardino, A., Mattei, F., Barra, A., & Businaro, L. (2014) · Scientific Reports · doi:10.1038/srep06639 · Cited by 91 · see citing works
Brown, A. J., Snapkov, I., Akbar, R., Pavlović, M., Miho, E., Sandve, G. K., & Greiff, V. (2019) · Molecular Systems Design & Engineering · doi:10.1039/c9me00071b · Cited by 59 · see citing works
Statistical physics of liquid brains
Piñero, J., & Solé, R. (2019) · Philosophical Transactions of the Royal Society B: Biological Sciences · doi:10.1098/rstb.2018.0376 · Cited by 39 · see citing works
Test of a Statistical Model for Molecular Recognition in Biological Repertoires
ROSENWALD, S., KAFRI, R., & LANCET, D. (2002) · Journal of Theoretical Biology · doi:10.1006/jtbi.2002.2538 · Cited by 37 · see citing works
Fundamental constraints to the logic of living systems
Solé, R., Kempes, C. P., Corominas-Murtra, B., De Domenico, M., Kolchinsky, A., Lachmann, M., Libby, E., Saavedra, S., Smith, E., & Wolpert, D. (2024) · Interface Focus · doi:10.1098/rsfs.2024.0010 · Cited by 34 · see citing works
Anergy in self-directed B lymphocytes: A statistical mechanics perspective
Agliari, E., Barra, A., Del Ferraro, G., Guerra, F., & Tantari, D. (2015) · Journal of Theoretical Biology · doi:10.1016/j.jtbi.2014.05.006 · Cited by 34 · see citing works
- Authors
- Perelson, A. S., & Weisbuch, G.
- Affiliations
- Los Alamos National Laboratory (US)
- ORCID
- Perelson, Alan S.
- Venue
- Reviews of Modern Physics
- Publisher
- American Physical Society (APS)
- Published
- 1997-10-01
- Volume
- 69
- Issue
- 4
- Pages
- 1219-1268
- ISSN
- 0034-6861 (ISSN-L)
- 1539-0756
- OpenAlex
- W1971201122
- Cited by
- 574
- References
- 2
- Citations by year
- 2026: 11 · 2025: 4 · 2024: 10 · 2023: 8 · 2022: 9 · 2021: 14 · 2020: 14 · 2019: 15 · 2018: 19 · 2017: 15 · 2016: 29 · 2015: 11 · 2014: 21 · 2013: 29 · 2012: 32
- FWCI
- 9.12
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Reviews of Modern Physics (publishedVersion)
- Topics
- Physical Sciences › Engineering › Biomedical Engineering › Artificial Immune Systems Applications
- Life Sciences › Immunology and Microbiology › Immunology › T-cell and B-cell Immunology
- Life Sciences › Immunology and Microbiology › Immunology › Immune Response and Inflammation
- Keywords
- immune system, pattern recognition, immunological memory, antigen recognition, intercellular communication, dynamical systems, immunology
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review