Quantitative Immunology for Physicists
arXiv:1907.03891 · doi:10.1016/j.physrep.2020.01.001
Abstract
The adaptive immune system is a dynamical, self-organized multiscale system that protects vertebrates from both pathogens and internal irregularities, such as tumours. For these reason it fascinates physicists, yet the multitude of different cells, molecules and sub-systems is often also petrifying. Despite this complexity, as experiments on different scales of the adaptive immune system become more quantitative, many physicists have made both theoretical and experimental contributions that help predict the behaviour of ensembles of cells and molecules that participate in an immune response. Here we review some recent contributions with an emphasis on quantitative questions and methodologies. We also provide a more general methods section that presents some of the wide array of theoretical tools used in the field.
arXiv comment78 page review
References in corpus (39)
- A high-bias, low-variance introduction to Machine Learning for physicists
- Kinetics of protein-DNA interaction: facilitated target location in sequence-dependent potential
- Robust estimation of microbial diversity in theory and in practice
- Maximum entropy models for antibody diversity
- Statistical inference of the generation probability of T-cell receptors from sequence repertoires
- Self-Organized Branching Processes: A Mean-Field Theory for Avalanches
- IGoR: a tool for high-throughput immune repertoire analysis
- Population genomics of intrapatient HIV-1 evolution
- Inverse statistical problems: from the inverse Ising problem to data science
- OLGA: fast computation of generation probabilities of B- and T-cell receptor amino acid sequences and motifs
- Predicting evolution from the shape of genealogical trees
- Genetic draft, selective interference, and population genetics of rapid adaptation
- Inferring processes underlying B-cell repertoire diversity
- Information transmission in genetic regulatory networks: a review
- The Value of Information for Populations in Varying Environments
- How a well-adapted immune system is organized
- Quantifying selection in immune receptor repertoires
- Measuring the sequence-affinity landscape of antibodies with massively parallel titration curves
- Consistency of VDJ rearrangement and substitution parameters enables accurate B cell receptor sequence annotation
- Replicate immunosequencing as a robust probe of B cell repertoire diversity
- Precise tracking of vaccine-responding T-cell clones reveals convergent and personalized response in identical twins
- Predicting the spectrum of TCR repertoire sharing with a data-driven model of recombination
- Absolute Rate Theories of Epigenetic Stability
- Likelihood-based inference of B-cell clonal families
- Fluctuating fitness shapes the clone size distribution of immune repertoires
- Self consistent proteomic field theory of stochastic gene switches
- Persisting fetal clonotypes influence the structure and overlap of adult human T cell receptor repertoires
- Using genotype abundance to improve phylogenetic inference
- How many different clonotypes do immune repertoires contain?
- Method for identification of condition-associated public antigen receptor sequences
- How a well-adapting immune system remembers
- Physical epistatic landscape of antibody binding affinity
- Thymic selection of T-cell receptors as an extreme value problem
- Principles of Adaptive Sorting Revealed by In Silico Evolution
- Mouse T cell repertoires as statistical ensembles: overall characterization and age dependence
- repgenHMM: a dynamic programming tool to infer the rules of immune receptor generation from sequence data
- Rényi entropy, abundance distribution and the equivalence of ensembles
- Untangling the hairball: fitness based asymptotic reduction of biological networks
- A model for the integration of conflicting exogenous and endogenous signals by dendritic cells
Cited by in corpus (4)
- Early life imprints the hierarchy of T cell clone sizes
- Immune cells use active tugging forces to distinguish affinity and accelerate evolution
- Extreme value statistics of positive recurrent centrally biased random walks
- Understanding how T helper cells learn to coordinate effective immune responses through the lens of reinforcement learning