How many TCR clonotypes does a body maintain?
Open accessAbstract
We consider the lifetime of a T cell clonotype, the set of T cells with the same T cell receptor, from its thymic origin to its extinction in a multiclonal repertoire. Using published estimates of total cell numbers and thymic production rates, we calculate the mean number of cells per TCR clonotype, and the total number of clonotypes, in mice and humans. When there is little peripheral division, as in a mouse, the number of cells per clonotype is small and governed by the number of cells with identical TCR that exit the thymus. In humans, peripheral division is important and a clonotype may survive for decades, during which it expands to comprise many cells. We therefore devise and analyse a computational model of homeostasis of a multiclonal population. Each T cell in the model competes for self pMHC stimuli, cells of any one clonotype only recognising a small fraction of the many subsets of stimuli. A constant mean total number of cells is maintained by a balance between cell division and death, and a stable number of clonotypes by a balance between thymic production of new clonotypes and extinction of existing ones. The number of distinct clonotypes in a human body may be smaller than the total number of naive T cells by only one order of magnitude.
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This estimate is consistent with TREC frequencies and with modeling predicting that the number of distinct human TCR sequences is only one order of magnitude lower than the number of total naive cells.
“This estimate is consistent with TREC frequencies as well as with modeling experiments which predict that the number of distinct sequences in humans is by only one order of magnitude lower than the number of total naive cells”
From Successful and Maladaptive T Cell Aging (2017) · cites this paper as Lythe et al., 2016
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Cites
Continuous Martingales and Brownian Motion
Revuz, D., & Yor, M. (1999) · Grundlehren der mathematischen Wissenschaften · doi:10.1007/978-3-662-06400-9 · Cited by 6,353 · see citing works
An Introduction to Stochastic Modeling
Frey, M. R., Taylor, H. M., & Karlin, S. (1994) · Technometrics · doi:10.2307/1269970 · Cited by 1,278 · see citing works
Comprehensive assessment of T-cell receptor β-chain diversity in αβ T cells
Robins, H. S., Campregher, P. V., Srivastava, S. K., Wacher, A., Turtle, C. J., Kahsai, O., Riddell, S. R., Warren, E. H., & Carlson, C. S. (2009) · Blood · doi:10.1182/blood-2009-04-217604 · Cited by 1,122 · see citing works
Stochastic Modelling for Systems Biology
Wilkinson, D. (2006) · Chapman & Hall/CRC eBooks · doi:10.1201/9781420010664 · Cited by 1,041 · see citing works
Moon, J. J., Chu, H., Pepper, M., McSorley, S. J., Jameson, S. C., Kedl, R. M., & Jenkins, M. K. (2007) · Immunity · doi:10.1016/j.immuni.2007.07.007 · Cited by 977 · see citing works
IL-7 is critical for homeostatic proliferation and survival of naïve T cells
Tan, J. T., Dudl, E. P., LeRoy, E., Murray, R. M., Sprent, J., Weinberg, K. I., & Surh, C. D. (2001) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.161126098 · Cited by 966 · see citing works
A very high level of crossreactivity is an essential feature of the T-cell receptor
Mason, D. (1998) · Immunology Today · doi:10.1016/s0167-5699(98)01299-7 · Cited by 950 · see citing works
A Direct Estimate of the Human αβ T Cell Receptor Diversity
Arstila, T. P., Casrouge, A., Baron, V., Even, J., Kanellopoulos, J., & Kourilsky, P. (1999) · Science · doi:10.1126/science.286.5441.958 · Cited by 931 · see citing works
Human memory T cells: generation, compartmentalization and homeostasis
Farber, D. L., Yudanin, N. A., & Restifo, N. P. (2014) · Nature Reviews Immunology · doi:10.1038/nri3567 · Cited by 897 · see citing works
The Influence of Age on T Cell Generation and TCR Diversity
Naylor, K., Li, G., Vallejo, A. N., Lee, W.-W., Koetz, K., Bryl, E., Witkowski, J., Fulbright, J., Weyand, C. M., & Goronzy, J. J. (2005) · The Journal of Immunology · doi:10.4049/jimmunol.174.11.7446 · Cited by 802 · see citing works
Selecting and maintaining a diverse T-cell repertoire
Goldrath, A. W., & Bevan, M. J. (1999) · Nature · doi:10.1038/46218 · Cited by 777 · see citing works
Diversity and clonal selection in the human T-cell repertoire
Qi, Q., Liu, Y., Cheng, Y., Glanville, J., Zhang, D., Lee, J.-Y., Olshen, R. A., Weyand, C. M., Boyd, S. D., & Goronzy, J. J. (2014) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1409155111 · Cited by 755 · see citing works
Handbook of Stochastic Methods for Physics, Chemistry and the Natural Sciences.
Gardiner, C. W., Bhat, U. N., Stoyan, D., Daley, D. J., Кутоянц, Ю. А., & Рао, Б. Л. С. П. (1986) · Biometrics · doi:10.2307/2531274 · Cited by 718 · see citing works
Selecting and maintaining a diverse T-cell repertoire
Goldrath, A. W., & Bevan, M. J. (1999) · Nature · doi:10.1038/35005508 · Cited by 714 · see citing works
The many important facets of T-cell repertoire diversity
Nikolich‐Žugich, J., Slifka, M. K., & Messaoudi, I. (2004) · Nature reviews. Immunology · doi:10.1038/nri1292 · Cited by 681 · see citing works
Perelson, A. S., & OSTER, G. F. (1979) · Journal of Theoretical Biology · doi:10.1016/0022-5193(79)90275-3 · Cited by 648 · see citing works
Lifespan of human lymphocyte subsets defined by CD45 isoforms
Michie, C. A., McLean, A. R., Alcock, C. J., & Beverley, P. C. L. (1992) · Nature · doi:10.1038/360264a0 · Cited by 635 · see citing works
Maintaining the norm: T-cell homeostasis
Jameson, S. C. (2002) · Nature reviews. Immunology · doi:10.1038/nri853 · Cited by 599 · see citing works
Spatial map of human T cell compartmentalization and maintenance over decades of life
Thome, J. J. C., Yudanin, N., Ohmura, Y., Kubota, M., Grinshpun, B., Sathaliyawala, T., Kato, T., Lerner, H., Shen, Y., & Farber, D. L. (2014) · Cell · doi:10.1016/j.cell.2014.10.026 · Cited by 587 · see citing works
Estimating the Precursor Frequency of Naive Antigen-specific CD8 T Cells
Blattman, J. N., Antia, R., Sourdive, D. J. D., Wang, X., Kaech, S. M., Murali‐Krishna, K., Altman, J. D., & Ahmed, R. (2002) · The Journal of Experimental Medicine · doi:10.1084/jem.20001021 · Cited by 583 · see citing works
Maintenance of peripheral naive T cells is sustained by thymus output in mice but not humans
den Braber, I., Mugwagwa, T., Vrisekoop, N., Westera, L., Mögling, R., Bregje de Boer, A., Willems, N., Schrijver, E. H. R., Spierenburg, G., Gaiser, K., et al. (2012) · Immunity · doi:10.1016/j.immuni.2012.02.006 · Cited by 572 · cited 11× · see citing works
“In our model, the thymus is a source of new T cell specificities, whereas division of T cells in the periphery can only contribute to the survival or expansion of existing clonotypes (den Braber et al., 2012).”
BackgroundMethodInfluentialThe many faces of IL-7: from lymphopoiesis to peripheral T cell maintenance
Fry, T. J., & Mackall, C. L. (2005) · The Journal of Immunology · doi:10.4049/jimmunol.174.11.6571 · Cited by 563 · see citing works
Deconstructing the Peptide-MHC Specificity of T Cell Recognition
Birnbaum, M. E., Mendoza, J. L., Sethi, D. K., Dong, S., Glanville, J., Dobbins, J., Özkan, E., Davis, M. M., Wucherpfennig, K. W., & García, K. C. (2014) · Cell · doi:10.1016/j.cell.2014.03.047 · Cited by 558 · see citing works
Scollay, R. G., Butcher, E. C., & Weissman, I. L. (1980) · European Journal of Immunology · doi:10.1002/eji.1830100310 · Cited by 555 · see citing works
Why must T cells be cross-reactive?
Sewell, A. K. (2012) · Nature reviews. Immunology · doi:10.1038/nri3279 · Cited by 544 · see citing works
Bipartite Graphs and their Applications
Asratian, A. S., Denley, T. M. J., & Häggkvist, R. (1998) · Cambridge University Press eBooks · doi:10.1017/cbo9780511984068 · Cited by 499 · see citing works
Normal T cell homeostasis: the conversion of naive cells into memory-phenotype cells
Sprent, J., & Surh, C. D. (2011) · Nature Immunology · doi:10.1038/ni.2018 · Cited by 480 · see citing works
Britanova, O. V., Putintseva, E. V., Shugay, M., Merzlyak, E. M., Turchaninova, M. A., Staroverov, D. B., Bolotin, D. A., Lukyanov, S., Bogdanova, E. A., Mamedov, I. Z., et al. (2014) · The Journal of Immunology · doi:10.4049/jimmunol.1302064 · Cited by 465 · see citing works
Interleukin 7 and T cell receptor signals regulate homeostasis of CD4 memory cells
Seddon, B. P., Tomlinson, P. D., & Zamoyska, R. (2003) · Nature Immunology · doi:10.1038/ni946 · Cited by 457 · see citing works
Virus-specific CD4(+) memory-phenotype T cells are abundant in unexposed adults
Su, L. F., Kidd, B. A., Han, A., Kotzin, J. J., & Davis, M. M. (2013) · Immunity · doi:10.1016/j.immuni.2012.10.021 · Cited by 429 · cited 2× · see citing works
“We take the value of p, the probability that interaction with a given self pMHC is capable of causing a randomly-selected T cell to divide, to be the same in humans and mice: p¼ 10 6 (Rizzuto et al., 2009; Su et al., 2013; Jenkins et al., 2009).”
BackgroundPopulation Biology of Lymphocytes: The Flight for Survival
Freitas, A. A., & Rocha, B. (2000) · Annual Review of Immunology · doi:10.1146/annurev.immunol.18.1.83 · Cited by 426 · see citing works
Origins of CD4+ effector and central memory T cells
Pepper, M., & Jenkins, M. K. (2011) · Nature Immunology · doi:10.1038/ni.2038 · Cited by 401 · see citing works
Naive T cell homeostasis: from awareness of space to a sense of place
Takada, K., & Jameson, S. C. (2009) · Nature reviews. Immunology · doi:10.1038/nri2657 · Cited by 375 · see citing works
Naïve and Memory CD4 + T Cell Survival Controlled by Clonal Abundance
Hataye, J. M., Moon, J. J., Khoruts, A., Reilly, C., & Jenkins, M. K. (2006) · Science · doi:10.1126/science.1124228 · Cited by 351 · see citing works
Warren, R. M., Freeman, J., Zeng, T., Choe, G. H., Munro, S., Moore, R., Webb, J. R., & Holt, R. A. (2011) · Genome Research · doi:10.1101/gr.115428.110 · Cited by 351 · see citing works
Weissman, I. L. (1967) · The Journal of Experimental Medicine · doi:10.1084/jem.126.2.291 · Cited by 347 · see citing works
Functional heterogeneity of human memory CD4 + T cell clones primed by pathogens or vaccines
Becattini, S., Latorre, D., Mele, F., Foglierini, M., Gregorio, C. D., Cassotta, A., Fernandez, B., Kelderman, S., Schumacher, T. N., Corti, D., et al. (2014) · Science · doi:10.1126/science.1260668 · Cited by 314 · see citing works
Size Estimate of the αβ TCR Repertoire of Naive Mouse Splenocytes
Casrouge, A., Beaudoing, E., Dalle, S., Pannetier, C., Kanellopoulos, J., & Kourilsky, P. (2000) · The Journal of Immunology · doi:10.4049/jimmunol.164.11.5782 · Cited by 312 · see citing works
Mandl, J. N., Monteiro, J. P., Vrisekoop, N., & Germain, R. N. (2013) · Immunity · doi:10.1016/j.immuni.2012.09.011 · Cited by 304 · see citing works
Košmrlj, A., Read, E. L., Qi, Y., Allen, T. M., Altfeld, M. A., Deeks, S. G., Pereyra, F., Carrington, M. N., Walker, B. D., & Chakraborty, A. K. (2010) · Nature · doi:10.1038/nature08997 · Cited by 301 · see citing works
Statistical inference of the generation probability of T-cell receptors from sequence repertoires
Murugan, A., Mora, T., Walczak, A. M., & Callan, C. G. (2012) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1212755109 · Cited by 292 · see citing works
Cold Spring Harbor Symposia on Quantitative Biology
(1937) · PROTOPLASMA · doi:10.1007/bf01625030 · Cited by 244 · see citing works
Quantifying T lymphocyte turnover
de Boer, R. J., & Perelson, A. S. (2013) · Journal of Theoretical Biology · doi:10.1016/j.jtbi.2012.12.025 · Cited by 241 · see citing works
Jenkins, M. K., Chu, H., McLachlan, J. B., & Moon, J. J. (2010) · Annual Review of Immunology · doi:10.1146/annurev-immunol-030409-101253 · Cited by 236 · see citing works
How Much TCR Does a T Cell Need?
Labrecque, N., Whitfield, S., Obst, R., Waltzinger, C., Benoist, C. O., & Mathis, D. J. (2001) · Immunity · doi:10.1016/s1074-7613(01)00170-4 · Cited by 231 · see citing works
Vrisekoop, N., den Braber, I., de Boer, A. B., Ruiter, A. F. C., Ackermans, M. T., van der Crabben, S. N., Schrijver, E. H. R., Spierenburg, G. T., Sauerwein, H. P., Hazenberg, M. D., et al. (2008) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0709713105 · Cited by 230 · see citing works
Evavold, B. D., Sloan‐Lancaster, J., Wilson, K. J., Rothbard, J. B., & Allen, P. M. (1995) · Immunity · doi:10.1016/1074-7613(95)90010-1 · Cited by 203 · see citing works
Immunosequencing: applications of immune repertoire deep sequencing
Robins, H. S. (2013) · Current Opinion in Immunology · doi:10.1016/j.coi.2013.09.017 · Cited by 199 · see citing works
Rapid Turnover of Effector–Memory CD4+ T Cells in Healthy Humans
Macallan, D. C., Wallace, D. L., Zhang, Y., de Lara, C., Worth, A. T., Ghattas, H., Griffin, G. E., Beverley, P. C. L., & Tough, D. F. (2004) · The Journal of Experimental Medicine · doi:10.1084/jem.20040341 · Cited by 193 · see citing works
Bousso, P., Casrouge, A., Altman, J. D., Haury, M., Kanellopoulos, J., Abastado, J., & Kourilsky, P. (1998) · Immunity · doi:10.1016/s1074-7613(00)80599-3 · Cited by 188 · see citing works
Estimating the Diversity, Completeness, and Cross-Reactivity of the T Cell Repertoire
Zarnitsyna, V. I., Evavold, B. D., Schoettle, L. N., Blattman, J. N., & Antia, R. (2013) · Frontiers in Immunology · doi:10.3389/fimmu.2013.00485 · Cited by 180 · see citing works
The Biology of Recent Thymic Emigrants
Fink, P. J. (2012) · Annual Review of Immunology · doi:10.1146/annurev-immunol-032712-100010 · Cited by 174 · see citing works
Thymic output: a bad TREC record
Hazenberg, M. D., Borghans, J. A. M., de Boer, R. J., & Miedema, F. F. (2003) · Nature Immunology · doi:10.1038/ni0203-97 · Cited by 164 · see citing works
A central role for thymic emigrants in peripheral T cell homeostasis
Berzins, S. P., Godfrey, D. I., Miller, J. F. A. P., & Boyd, R. L. (1999) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.96.17.9787 · Cited by 163 · see citing works
Almeida, A. R. M., Borghans, J. A. M., & Freitas, A. A. (2001) · The Journal of Experimental Medicine · doi:10.1084/jem.194.5.591 · Cited by 163 · see citing works
Towards a general function describing t cell proliferation
de Boer, R. J., & Perelson, A. S. (1995) · Journal of Theoretical Biology · doi:10.1006/jtbi.1995.0165 · Cited by 162 · see citing works
Quantifying the development of the peripheral naive CD4+ T-cell pool in humans
Bains, I., Antia, R., Callard, R. E., & Yates, A. J. (2009) · Blood · doi:10.1182/blood-2008-10-184184 · Cited by 153 · see citing works
Self-citationRudd, B. D., Venturi, V., Li, G., Samadder, P. P., Ertelt, J. M., Way, S. S., Davenport, M. P., & Nikolich‐Žugich, J. (2011) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1107594108 · Cited by 149 · see citing works
Min, B., Foucras, G., Meier‐Schellersheim, M., & Paul, W. E. (2004) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0400606101 · Cited by 148 · see citing works
Quantifying selection in immune receptor repertoires
Elhanati, Y., Murugan, A., Callan, C. G., Mora, T., & Walczak, A. M. (2014) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1409572111 · Cited by 145 · see citing works
Westera, L., Drylewicz, J., den Braber, I., Mugwagwa, T., van der Maas, I., Kwast, L., Volman, T., van de Weg-Schrijver, E. H. R., Bartha, I., Spierenburg, G., et al. (2013) · Blood · doi:10.1182/blood-2013-03-488411 · Cited by 136 · see citing works
Tanchot, C., Rosado, M. M., Agenès, F., Freitas, A. A., & Rocha, B. (1997) · Seminars in Immunology · doi:10.1006/smim.1997.0090 · Cited by 134 · see citing works
Murray, J. M., Kaufmann, G. R., Hodgkin, P. D., Lewin, S. R., Kelleher, A. D., Davenport, M. P., & Zaunders, J. J. (2003) · Immunology and Cell Biology · doi:10.1046/j.1440-1711.2003.01191.x · Cited by 132 · see citing works
Bains, I., Thiébaut, R., Yates, A. J., & Callard, R. E. (2009) · The Journal of Immunology · doi:10.4049/jimmunol.0900743 · Cited by 131 · see citing works
Self-citationTroy, A. E., & Shen, H. (2003) · The Journal of Immunology · doi:10.4049/jimmunol.170.2.672 · Cited by 123 · see citing works
Competition for self ligands restrains homeostatic proliferation of naive CD4 T cells
Moses, C. T., Thorstenson, K. M., Jameson, S. C., & Khoruts, A. (2003) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0334572100 · Cited by 122 · see citing works
T cell homeostasis: Keeping useful T cells alive and live T cells useful
Jameson, S. C. (2005) · Seminars in Immunology · doi:10.1016/j.smim.2005.02.003 · Cited by 118 · see citing works
Methods for diversity and overlap analysis in T-cell receptor populations
Rempała, G. A., & Seweryn, M. T. (2012) · Journal of Mathematical Biology · doi:10.1007/s00285-012-0589-7 · Cited by 117 · see citing works
Langman, R. E., & Cohn, M. (1987) · Molecular Immunology · doi:10.1016/0161-5890(87)90050-2 · Cited by 117 · see citing works
Thymic regeneration: teaching an old immune system new tricks
Berzins, S. P., Uldrich, A. P., Sutherland, J. S., Gill, J. W., MILLER, J. F. A. P., Godfrey, D. I., & Boyd, R. L. (2002) · Trends in Molecular Medicine · doi:10.1016/s1471-4914(02)02415-2 · Cited by 114 · see citing works
Rizzuto, G. A., Merghoub, T., Hirschhorn-Cymerman, D., Liu, C., Lesokhin, A. M., Sahawneh, D., Zhong, H., Panageas, K. S., Perales, M., Altan-Bonnet, G. Y., et al. (2009) · The Journal of Experimental Medicine · doi:10.1084/jem.20081382 · Cited by 113 · see citing works
Thomas, N., Best, K., Cinelli, M., Reich-Zeliger, S., Gal, H., Shifrut, E., Madi, A., Friedman, N., Shawe-Taylor, J. S., & Chain, B. (2014) · Bioinformatics · doi:10.1093/bioinformatics/btu523 · Cited by 105 · see citing works
Binomial tau-leap spatial stochastic simulation algorithm for applications in chemical kinetics
Marquez‐Lago, T. T., & Burrage, K. (2007) · The Journal of Chemical Physics · doi:10.1063/1.2771548 · Cited by 103 · see citing works
Theories and Quantification of Thymic Selection
Yates, A. J. (2014) · Frontiers in Immunology · doi:10.3389/fimmu.2014.00013 · Cited by 99 · see citing works
An introduction to stochastic modeling
(1994) · Choice Reviews Online · doi:10.5860/choice.31-5510 · Cited by 99 · see citing works
Lymphocyte maintenance during healthy aging requires no substantial alterations in cellular turnover
Westera, L., van Hoeven, V., Drylewicz, J., Spierenburg, G., van Velzen, J. F., de Boer, R. J., Tesselaar, K., & Borghans, J. A. M. (2015) · Aging Cell · doi:10.1111/acel.12311 · Cited by 96 · see citing works
Johnson, P. L. F., Yates, A. J., Goronzy, J. J., & Antia, R. (2012) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1209283110 · Cited by 94 · see citing works
Mathematical Modeling Reveals Kinetics of Lymphocyte Recirculation in the Whole Organism
Ganusov, V. V., & Auerbach, J. (2014) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1003586 · Cited by 93 · see citing works
Asymmetric thymocyte death underlies the CD4:CD8 T-cell ratio in the adaptive immune system
Sinclair, C., Bains, I., Yates, A. J., & Seddon, B. P. (2013) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1304859110 · Cited by 90 · see citing works
Maintaining system homeostasis: the third law of Newtonian immunology
Germain, R. N. (2012) · Nature Immunology · doi:10.1038/ni.2404 · Cited by 88 · see citing works
Comprehensive Assessment and Mathematical Modeling of T Cell Population Dynamics and Homeostasis
Thomas‐Vaslin, V., Altes, H. K., de Boer, R. J., & Klatzmann, D. (2008) · The Journal of Immunology · doi:10.4049/jimmunol.180.4.2240 · Cited by 86 · see citing works
Calis, J. J. A., de Boer, R. J., & Keşmir, C. (2012) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1002412 · Cited by 85 · see citing works
Laethem, F. V., Tikhonova, A. N., & Singer, A. (2012) · Trends in Immunology · doi:10.1016/j.it.2012.05.006 · Cited by 84 · see citing works
TCR signaling requirements for activating T cells and for generating memory
Zehn, D., King, C. G., Bevan, M. J., & Palmer, E. (2012) · Cellular and Molecular Life Sciences · doi:10.1007/s00018-012-0965-x · Cited by 81 · see citing works
Diversity of Human αβ T Cell Receptors
Keşmir, C., Borghans, J. A. M., & de Boer, R. J. (2000) · Science · doi:10.1126/science.288.5469.1135a · Cited by 80 · see citing works
CD69 Expression Discriminates MHC-Dependent and -Independent Stages of Thymocyte Positive Selection
Hare, K. J., Jenkinson, E. J., & Anderson, G. (1999) · The Journal of Immunology · doi:10.4049/jimmunol.162.7.3978 · Cited by 79 · see citing works
A Reliable and Safe T Cell Repertoire based on Low-affinity T Cell Receptors
van den Berg, H. A., Rand, D. A. J., & Burroughs, N. J. (2001) · Journal of Theoretical Biology · doi:10.1006/jtbi.2001.2281 · Cited by 78 · see citing works
Antia, R., Pilyugin, S. S., & Ahmed, R. (1998) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.95.25.14926 · Cited by 78 · see citing works
Method for assessing the similarity between subsets of the T cell receptor repertoire
Venturi, V., Kedzierska, K., Tanaka, M. M., Turner, S. J., Doherty, P. C., & Davenport, M. P. (2007) · Journal of Immunological Methods · doi:10.1016/j.jim.2007.09.016 · Cited by 77 · see citing works
Quantification of T‐cell dynamics: from telomeres to DNA labeling
Borghans, J. A. M., & de Boer, R. J. (2007) · Immunological Reviews · doi:10.1111/j.1600-065x.2007.00497.x · Cited by 76 · see citing works
Discriminating self from nonself with short peptides from large proteomes
Burroughs, N. J., de Boer, R. J., & Keşmir, C. (2004) · Immunogenetics · doi:10.1007/s00251-004-0691-0 · Cited by 73 · see citing works
Signaling thresholds govern heterogeneity in IL‐7‐receptor‐mediated responses of naïve CD8+ T cells
Palmer, M. J., Mahajan, V. S., Chen, J., Irvine, D. J., & Lauffenburger, D. A. (2011) · Immunology and Cell Biology · doi:10.1038/icb.2011.5 · Cited by 72 · see citing works
Hare, K. J., Jenkinson, E. J., & Anderson, G. (2000) · The Journal of Immunology · doi:10.4049/jimmunol.165.5.2410 · Cited by 71 · see citing works
Recent thymic emigrants are preferentially incorporated only into the depleted T-cell pool
Houston, E. G., Higdon, L. E., & Fink, P. J. (2011) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1015286108 · Cited by 69 · see citing works
How Specific Should Immunological Memory Be?
Borghans, J. A. M., Noest, A. J., & de Boer, R. J. (1999) · The Journal of Immunology · doi:10.4049/jimmunol.163.2.569 · Cited by 69 · see citing works
Newell, E. W., Ely, L. K., Kruse, A. C., Reay, P. A., Rodriguez, S. N., Lin, A. E., Kuhns, M. S., García, K. C., & Davis, M. M. (2011) · The Journal of Immunology · doi:10.4049/jimmunol.1100197 · Cited by 66 · see citing works
Bourgeois, C., Hao, Z., Rajewsky, K., Potocnik, A. J., & Stockinger, B. (2008) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.0803732105 · Cited by 64 · see citing works
Mutually exclusive regulation of T cell survival by IL-7R and antigen receptor-induced signals
Koenen, P., Heinzel, S., Carrington, E. M., Happo, L., Alexander, W. S., Zhang, J., Herold, M. J., Scott, C. L., Lew, A. M., Strasser, A., et al. (2013) · Nature Communications · doi:10.1038/ncomms2719 · Cited by 61 · see citing works
Thomas, P. G., Handel, A., Doherty, P. C., & Gruta, N. L. L. (2013) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1222149110 · Cited by 52 · see citing works
Stochastic Population Processes: Analysis, Approximations, Simulations
Renshaw, E. (2011) · Cited by 49 · see citing works
Homeostasis of T cell diversity.
Mahajan, V. S., Leskov, I. B., & Chen, J. Z. (2005) · PubMed · Cited by 46 · see citing works
The clone size of peripheral CD8 T cells is regulated by TCR promiscuity
Hao, Y., Legrand, N., & Freitas, A. A. (2006) · The Journal of Experimental Medicine · doi:10.1084/jem.20052174 · Cited by 46 · see citing works
Quantitative theories of T‐cell responsiveness
van den Berg, H. A., & Rand, D. A. J. (2007) · Immunological Reviews · doi:10.1111/j.1600-065x.2006.00491.x · Cited by 45 · see citing works
Competitive control of the self-renewing T cell repertoire
de Boer, R. J. (1997) · International Immunology · doi:10.1093/intimm/9.5.779 · Cited by 45 · see citing works
Stochastic niche structure and diversity maintenance in the T cell repertoire
Stirk, E. R., Molina-Parı́s, C., & van den Berg, H. A. (2008) · Journal of Theoretical Biology · doi:10.1016/j.jtbi.2008.07.017 · Cited by 43 · see citing works
Self-citationBosco, N., Agenès, F., & Ceredig, R. H. (2005) · The Journal of Immunology · doi:10.4049/jimmunol.175.1.162 · Cited by 42 · see citing works
Singh, N. J., Bando, J. K., & Schwartz, R. H. (2012) · Immunity · doi:10.1016/j.immuni.2012.08.008 · Cited by 40 · see citing works
Clonally Diverse T Cell Homeostasis Is Maintained by a Common Program of Cell-Cycle Control
Hogan, T. V., Shuvaev, А. N., Commenges, D., Yates, A. J., Callard, R. E., Thiébaut, R., & Seddon, B. P. (2013) · The Journal of Immunology · doi:10.4049/jimmunol.1203213 · Cited by 38 · see citing works
Self-citationSinclair, C., Saini, M., van der Loeff, I. S., Sakaguchi, S., & Seddon, B. P. (2011) · Science Signaling · doi:10.1126/scisignal.2002246 · Cited by 36 · see citing works
The Rate of Immune Escape Vanishes When Multiple Immune Responses Control an HIV Infection
van Deutekom, H. W. M., Wijnker, G., & de Boer, R. J. (2013) · The Journal of Immunology · doi:10.4049/jimmunol.1300962 · Cited by 34 · see citing works
Regulation of peripheral T-cell homeostasis by receptor signalling
Seddon, B. P., & Zamoyska, R. (2003) · Current Opinion in Immunology · doi:10.1016/s0952-7915(03)00049-9 · Cited by 33 · see citing works
Multivariate Competition Processes
Iglehart, D. L. (1964) · The Annals of Mathematical Statistics · doi:10.1214/aoms/1177703758 · Cited by 32 · see citing works
Bergot, A., Chaara, W., Ruggiero, E., Mariotti‐Ferrandiz, E., Dulauroy, S., Schmidt, M., Kalle, C. V., Six, A., & Klatzmann, D. (2015) · European Journal of Immunology · doi:10.1002/eji.201445269 · Cited by 28 · see citing works
Ciupe, S. M., Devlin, B. H., Markert, M. L., & Kepler, T. B. (2009) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1000396 · Cited by 26 · see citing works
Paul, W. E., Milner, J. D., & Grossman, Z. (2013) · Cold Spring Harbor Symposia on Quantitative Biology · doi:10.1101/sqb.2013.78.020198 · Cited by 24 · see citing works
TCR Triggering by the pMHC Complex: Valency, Affinity, and Dynamics
Varma, R. (2008) · Science Signaling · doi:10.1126/stke.119pe21 · Cited by 24 · see citing works
Modelling deuterium labelling of lymphocytes with temporal and/or kinetic heterogeneity
de Boer, R. J., Perelson, A. S., & Ribeiro, R. M. (2012) · Journal of The Royal Society Interface · doi:10.1098/rsif.2012.0149 · Cited by 24 · see citing works
Quantification of total T-cell receptor diversity by flow cytometry and spectratyping
Ciupe, S. M., Devlin, B. H., Markert, M. L., & Kepler, T. B. (2013) · BMC Immunology · doi:10.1186/1471-2172-14-35 · Cited by 22 · see citing works
Efficient characterization of the TCR repertoire in lymph nodes by flow cytometry
Salameire, D., Bris, Y. L., Fabre, B., Fauconnier, J., Solly, F., Pernollet, M., Bonnefoix, T., Leroux, D., Plumas, J., & Jacob, M. (2009) · Cytometry Part A · doi:10.1002/cyto.a.20767 · Cited by 22 · see citing works
Leitão, C., Freitas, A. A., & Garcia, S. (2009) · The Journal of Immunology · doi:10.4049/jimmunol.0804071 · Cited by 20 · see citing works
Monitoring the Dynamics of T Cell Clonal Diversity Using Recombinant Peptide:MHC Technology
Blanchfield, L., Shorter, S. K., & Evavold, B. D. (2013) · Frontiers in Immunology · doi:10.3389/fimmu.2013.00170 · Cited by 19 · see citing works
Tamargo, B., Nápoles, Y. M., González, W. R., Cedré, B., Fresno, M., & Sierra, G. (2013) · BMC Immunology · doi:10.1186/1471-2172-14-s1-s12 · Cited by 18 · see citing works
The Thymus in Immunity and in Malignancy
von Boehmer, H. (2014) · Cancer Immunology Research · doi:10.1158/2326-6066.cir-14-0070 · Cited by 18 · see citing works
Agenès, F., Dangy, J., & Kirberg, J. (2008) · The Journal of Experimental Medicine · doi:10.1084/jem.20070467 · Cited by 17 · see citing works
Stirk, E. R., Lythe, G., van den Berg, H. A., Hurst, G. A. D., & Molina-Parı́s, C. (2010) · Mathematical Biosciences · doi:10.1016/j.mbs.2009.12.004 · Cited by 16 · see citing works
Self-citationPearson, C. F., SILVA, A. C. F. D., Saini, M. K., & Seddon, B. P. (2011) · European Journal of Immunology · doi:10.1002/eji.201141514 · Cited by 14 · see citing works
Development of the T-Cell Repertoire: of Clone Size Distribution
Merrill, S. J., DEBOER, R., & Perelson, A. S. (1993) · Rocky Mountain Journal of Mathematics · doi:10.1216/rmjm/1181072462 · Cited by 11 · see citing works
Nota Bene: Population Biology of Lymphocytes
Gallagher, R. B. (1997) · Science · doi:10.1126/science.276.5320.1817 · Cited by 11 · see citing works
How Does Cross-Reactive Stimulation Affect the Longevity of CD8+ T Cell Memory?
Ganusov, V. V., Pilyugin, S. S., Ahmed, R., & Antia, R. (2006) · PLoS Computational Biology · doi:10.1371/journal.pcbi.0020055 · Cited by 8 · see citing works
Thomas, N., Best, K., Cinelli, M., et al. (2014) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/001883 · Cited by 8 · see citing works
Quantifying selection in immune receptor repertoiresPreprint
Elhanati, Y., Murugan, A., Callan, C. G., et al. (2014) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/004341 · Cited by 8 · see citing works
Correction: How Does Cross-Reactive Stimulation Affect the Longevity of CD8+ T Cell Memory?
Ganusov, V. V., Pilyugin, S. S., Ahmed, R., & Antia, R. (2006) · PLoS Computational Biology · doi:10.1371/journal.pcbi.0020097 · Cited by 4 · see citing works
Multivariate Competition Processes: A Model for Two Competing T Cell Clonotypes
Molina-Parı́s, C., Lythe, G., & Stirk, E. R. (2011) · Springer eBooks · doi:10.1007/978-1-4419-7725-0_9 · Cited by 2 · see citing works
Self-citationBe fruitful, multiply, and replenish
Borghans, J. A. M., & Tesselaar, K. (2009) · Blood · doi:10.1182/blood-2009-03-207266 · Cited by 2 · see citing works
Continuous-Time Birth and Death Processes: Diversity Maintenance of Naïve T Cells in the Periphery
Molina-Parı́s, C., Stirk, E. R., Quinn, K., & Lythe, G. (2011) · Springer eBooks · doi:10.1007/978-1-4419-7725-0_8 · Cited by 2 · see citing works
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Mechanisms underlying T cell ageing
Goronzy, J. J., & Weyand, C. M. (2019) · Nature Reviews Immunology · doi:10.1038/s41577-019-0180-1 · Cited by 506 · see citing works
Successful and Maladaptive T Cell Aging
Goronzy, J. J., & Weyand, C. M. (2017) · Immunity · doi:10.1016/j.immuni.2017.03.010 · Cited by 362 · see citing works
Principles and therapeutic applications of adaptive immunity
Chi, H., Pepper, M., & Thomas, P. G. (2024) · Cell · doi:10.1016/j.cell.2024.03.037 · Cited by 363 · see citing works
Cancer Therapy With TCR-Engineered T Cells: Current Strategies, Challenges, and Prospects
Shafer, P. W., Somes, L. K., & Hoyos, V. (2022) · Frontiers in Immunology · doi:10.3389/fimmu.2022.835762 · Cited by 280 · see citing works
Sethna, Z. M., Elhanati, Y., Callan, C. G., Walczak, A. M., & Mora, T. (2019) · Bioinformatics · doi:10.1093/bioinformatics/btz035 · Cited by 227 · see citing works
Mathematical Models for Immunology: Current State of the Art and Future Research Directions
Eftimie, R., Gillard, J. J., & Cantrell, D. A. (2016) · Bulletin of Mathematical Biology · doi:10.1007/s11538-016-0214-9 · Cited by 213 · see citing works
The landscape of T cell antigens for cancer immunotherapy
Peri, A., Salomon, N., Wolf, Y., Kreiter, S., Diken, M., & Samuels, Y. (2023) · Nature Cancer · doi:10.1038/s43018-023-00588-x · Cited by 130 · see citing works
Predicting the spectrum of TCR repertoire sharing with a data‐driven model of recombination
Elhanati, Y., Sethna, Z., Callan, C. G., Mora, T., & Walczak, A. M. (2018) · Immunological Reviews · doi:10.1111/imr.12665 · Cited by 122 · see citing works
Wang, P., Yao, L., Luo, M., Zhou, W., Jin, X., Xu, Z., Shi, Y., Li, Y., Xu, C., Cheng, R., et al. (2021) · Cell Discovery · doi:10.1038/s41421-021-00280-3 · Cited by 123 · see citing works
Oakes, T., Heather, J., Best, K., Byng-Maddick, R., Husovsky, C., Ismail, M., Joshi, K., Maxwell, G., Noursadeghi, M., Riddell, N. E., et al. (2017) · Frontiers in Immunology · doi:10.3389/fimmu.2017.01267 · Cited by 116 · see citing works
Genesis of the αβ T-cell receptor
Dupic, T., Marcou, Q., Walczak, A. M., & Mora, T. (2019) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1006874 · Cited by 107 · see citing works
Sun, X., Nguyen, T. B. V., Achour, A., Ko, A., Cifello, J., Ling, C., Sharma, J., Hiroi, T., Zhang, Y., Chia, C. W., et al. (2022) · Journal of Clinical Investigation · doi:10.1172/jci158122 · Cited by 107 · see citing works
The immuneML ecosystem for machine learning analysis of adaptive immune receptor repertoires
Pavlović, M., Scheffer, L., Motwani, K., Kanduri, C., Kompova, R., Vazov, N., Waagan, K., Bernal, F. L. M., da Costa, A. A., Corrie, B., et al. (2021) · Nature Machine Intelligence · doi:10.1038/s42256-021-00413-z · Cited by 89 · see citing works
cGAS-STING pathway as a potential trigger of immunosenescence and inflammaging
Schmitz, C. R. R., Maurmann, R. M., Guma, F. T. C. R., Bauer, M. E., & Barbé‐Tuana, F. M. (2023) · Frontiers in Immunology · doi:10.3389/fimmu.2023.1132653 · Cited by 91 · see citing works
The naive T-cell receptor repertoire has an extremely broad distribution of clone sizes
de Greef, P. C., Oakes, T., Gerritsen, B., Ismail, M., Heather, J., Hermsen, R., Chain, B., & de Boer, R. J. (2020) · eLife · doi:10.7554/elife.49900 · Cited by 88 · see citing works
How many different clonotypes do immune repertoires contain?
Mora, T., & Walczak, A. M. (2019) · Current Opinion in Systems Biology · doi:10.1016/j.coisb.2019.10.001 · Cited by 85 · see citing works
ATM-TCR: TCR-Epitope Binding Affinity Prediction Using a Multi-Head Self-Attention Model
Cai, M., Bang, S., Zhang, P., & Lee, H. (2022) · Frontiers in Immunology · doi:10.3389/fimmu.2022.893247 · Cited by 82 · see citing works
From thymus to tissues and tumors: A review of T-cell biology
Chopp, L. B., Redmond, C., O’Shea, J. J., & Schwartz, D. M. (2022) · Journal of Allergy and Clinical Immunology · doi:10.1016/j.jaci.2022.10.011 · Cited by 85 · see citing works
Biomaterials to enhance antigen-specific T cell expansion for cancer immunotherapy
Isser, A., Livingston, N. K., & Schneck, J. P. (2020) · Biomaterials · doi:10.1016/j.biomaterials.2020.120584 · Cited by 77 · see citing works
T-cell repertoire diversity: friend or foe for protective antitumor response?
Porciello, N., Franzese, O., D’Ambrosio, L., Palermo, B., & Nisticò, P. (2022) · Journal of Experimental & Clinical Cancer Research · doi:10.1186/s13046-022-02566-0 · Cited by 82 · see citing works
Aversa, I., Malanga, D., Fiume, G., & Palmieri, C. (2020) · International Journal of Molecular Sciences · doi:10.3390/ijms21072378 · Cited by 71 · see citing works
Christley, S., Scarborough, W., Salinas, E., Rounds, W. H., Toby, I. T., Fonner, J. M., Levin, M. K., Kim, M., Mock, S. A., Jordan, C., et al. (2018) · Frontiers in Immunology · doi:10.3389/fimmu.2018.00976 · Cited by 72 · see citing works
Explaining A Black-box By Using A Deep Variational Information Bottleneck Approach
Bang, S., Xie, P., Lee, H., Wu, W., & Xing, E. P. (2021) · Proceedings of the AAAI Conference on Artificial Intelligence · doi:10.1609/aaai.v35i13.17358 · Cited by 69 · see citing works
Quantitative immunology for physicists
Altan-Bonnet, G. Y., Mora, T., & Walczak, A. M. (2020) · Physics Reports · doi:10.1016/j.physrep.2020.01.001 · Cited by 58 · see citing works
Developing combination strategies using PD-1 checkpoint inhibitors to treat cancer
Schmidt, E. V. (2018) · Seminars in Immunopathology · doi:10.1007/s00281-018-0714-9 · Cited by 62 · see citing works
Sex bias in MHC I-associated shaping of the adaptive immune system
Schneider‐Hohendorf, T., Görlich, D., Savola, P., Kelkka, T., Mustjoki, S. M., Groß, C. C., Owens, G. C., Klotz, L., Dornmair, K., Wiendl, H., et al. (2018) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1716146115 · Cited by 58 · see citing works
Stitchr: stitching coding TCR nucleotide sequences from V/J/CDR3 information
Heather, J., Spindler, M. J., Alonso, M. H., Shui, Y., Millar, D. G., Johnson, D. S., Cobbold, M., & Hata, A. N. (2022) · Nucleic Acids Research · doi:10.1093/nar/gkac190 · Cited by 57 · see citing works
GVHD Pathogenesis, Prevention and Treatment: Lessons From Humanized Mouse Transplant Models
Hess, N. J., Brown, M. E., & Capitini, C. M. (2021) · Frontiers in Immunology · doi:10.3389/fimmu.2021.723544 · Cited by 56 · see citing works
MHC-II alleles shape the CDR3 repertoires of conventional and regulatory naïve CD4 + T cells
Logunova, N. N., Kriukova, V., Shelyakin, P. V., Egorov, E. S., Pereverzeva, A. R., Bozhanova, N. G., Shugay, M., Shcherbinin, D. S., Pogorelyy, M. V., Merzlyak, E. M., et al. (2020) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2003170117 · Cited by 55 · see citing works
Using the T Cell Receptor as a Biomarker in Type 1 Diabetes
Nakayama, M., & Michels, A. W. (2021) · Frontiers in Immunology · doi:10.3389/fimmu.2021.777788 · Cited by 48 · see citing works
Quantifying lymphocyte receptor diversityPreprint
Mora, T., & Walczak, A. M. (2016) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/046870 · Cited by 53 · see citing works
Early life imprints the hierarchy of T cell clone sizes
Gaimann, M. U., Nguyen, M., Desponds, J., & Mayer, A. (2020) · eLife · doi:10.7554/elife.61639 · Cited by 50 · see citing works
Mathematics in modern immunology
Castro, M., Lythe, G., Molina-Parı́s, C., & Ribeiro, R. M. (2016) · Interface Focus · doi:10.1098/rsfs.2015.0093 · Cited by 46 · see citing works
Self-citationInferring the immune response from repertoire sequencing
Touzel, M. P., Walczak, A. M., & Mora, T. (2020) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1007873 · Cited by 46 · see citing works
On being the right size: antibody repertoire formation in the mouse and human
Collins, A. M., & Jackson, K. (2017) · Immunogenetics · doi:10.1007/s00251-017-1049-8 · Cited by 45 · see citing works
Modeling human T1D-associated autoimmune processes
Maharlooei, M. K., Madley, R., Borsotti, C., Ferreira, L. M. R., Sharp, R. C., Brehm, M. A., Greiner, D. L., Parent, A. V., Anderson, M. S., Sykes, M., et al. (2021) · Molecular Metabolism · doi:10.1016/j.molmet.2021.101417 · Cited by 42 · see citing works
The Goldilocks Window of Personalized Chemotherapy: Getting the Immune Response Just Right
Park, D. S., Robertson‐Tessi, M., Luddy, K. A., Maini, P. K., Bonsall, M. B., Gatenby, R. A., & Anderson, A. R. A. (2019) · Cancer Research · doi:10.1158/0008-5472.can-18-3712 · Cited by 41 · see citing works
Age as a risk factor in vasculitis
Gloor, A. D., Berry, G. J., Goronzy, J. J., & Weyand, C. M. (2022) · Seminars in Immunopathology · doi:10.1007/s00281-022-00911-1 · Cited by 43 · see citing works
Autoimmunity (or Not) in Atopic Dermatitis
Roesner, L. M., & Werfel, T. (2019) · Frontiers in Immunology · doi:10.3389/fimmu.2019.02128 · Cited by 38 · see citing works
Diversity in biology: definitions, quantification and models
Xu, S., Böttcher, L., & Chou, T. (2020) · Physical Biology · doi:10.1088/1478-3975/ab6754 · Cited by 37 · see citing works
Guo, L., Bi, X., Li, Y., Li, W., Zhang, W., Jiang, W., Ma, J., Feng, L., Zhang, K., & Shou, J. (2020) · The Journal of Pathology · doi:10.1002/path.5396 · Cited by 35 · see citing works
Machine Learning Approaches to TCR Repertoire Analysis
Katayama, Y., Yokota, R., Akiyama, T., & Kobayashi, T. (2022) · Frontiers in Immunology · doi:10.3389/fimmu.2022.858057 · Cited by 33 · see citing works
The natural history of naive T cells from birth to maturity
Seddon, B. P., & Yates, A. J. (2018) · Immunological Reviews · doi:10.1111/imr.12694 · Cited by 33 · see citing works
Autoreactive T cell receptors with shared germline-like α chains in type 1 diabetes
Linsley, P. S., Barahmand-pour-Whitman, F., Balmas, E., DeBerg, H. A., Flynn, K. J., Hu, A. K., Rosasco, M. G., Chen, J., O’Rourke, C., Serti, E., et al. (2021) · JCI Insight · doi:10.1172/jci.insight.151349 · Cited by 33 · see citing works
Machine Learning Applications in Solid Organ Transplantation and Related Complications
Balch, J. A., Delitto, D., Tighe, P. J., Zarrinpar, A., Efron, P. A., Rashidi, P., Upchurch, G. R., Bihorac, A., & Loftus, T. J. (2021) · Frontiers in Immunology · doi:10.3389/fimmu.2021.739728 · Cited by 33 · see citing works
T Cell Development and Function
Adu‐Berchie, K., Obuseh, F. O., & Mooney, D. J. (2023) · Rejuvenation Research · doi:10.1089/rej.2023.0015 · Cited by 30 · see citing works
Amoriello, R., Mariottini, A., & Ballerini, C. (2021) · Frontiers in Immunology · doi:10.3389/fimmu.2021.799380 · Cited by 29 · see citing works
Leary, A. Y., Scott, D., Gupta, N. T., Waite, J. C., Skokos, D., Atwal, G. S., & Hawkins, P. G. (2024) · Nature Communications · doi:10.1038/s41467-024-48198-0 · Cited by 29 · see citing works
What a Clinical Hematologist Should Know about T Cells?
Sharma, S. K. (2020) · International Blood Research & Reviews · doi:10.9734/ibrr/2020/v11i430137 · Cited by 27 · see citing works
Two types of human TCR differentially regulate reactivity to self and non-self antigens
Trofimov, A., Brouillard, P., Larouche, J., Séguin, J., Laverdure, J., Brasey, A., Ehx, G., Roy, D., Busque, L., Lachance, S., et al. (2022) · iScience · doi:10.1016/j.isci.2022.104968 · Cited by 28 · see citing works
Lanfermeijer, J., Borghans, J. A. M., & van Baarle, D. (2020) · Aging Cell · doi:10.1111/acel.13262 · Cited by 26 · see citing works
Recall T cell responses to bluetongue virus produce a narrowing of the T cell repertoire
Rojas, J. M., Calvo, T. R., & Sevilla, N. (2017) · Veterinary Research · doi:10.1186/s13567-017-0444-3 · Cited by 25 · see citing works
Bortone, D. S., Woodcock, M. G., Parker, J. S., & Vincent, B. G. (2020) · Cancer Immunology Research · doi:10.1158/2326-6066.cir-20-0398 · Cited by 24 · see citing works
Myronov, A., Mazzocco, G., Król, P., & Plewczyński, D. (2023) · Bioinformatics · doi:10.1093/bioinformatics/btad468 · Cited by 24 · see citing works
Some deterministic and stochastic mathematical models of naïve T‐cell homeostasis
Lythe, G., & Molina-Parı́s, C. (2018) · Immunological Reviews · doi:10.1111/imr.12696 · Cited by 22 · see citing works
Self-citationPhage display enables machine learning discovery of cancer antigen–specific TCRs
Croce, G., Lani, R., Tardivon, D., Bobisse, S., de Tiani, M., Bragina, M., Perez, M. A. S., Michaux, J., Pak, H. S., Michel, A., et al. (2025) · Science Advances · doi:10.1126/sciadv.ads5589 · Cited by 23 · see citing works
Universal CAR 2.0 to overcome current limitations in CAR therapy
Schlegel, L. S., Werbrouck, C., Boettcher, M., & Schlegel, P. (2024) · Frontiers in Immunology · doi:10.3389/fimmu.2024.1383894 · Cited by 21 · see citing works
Shang, B., Guo, L., Shen, R., Cao, C., Xie, R., Jiang, W., Wen, L., Bi, X., Shi, H., Zheng, S., et al. (2021) · Frontiers in Oncology · doi:10.3389/fonc.2021.771545 · Cited by 21 · see citing works
Impact of TCR Diversity on the Development of Transplanted or Chemically Induced Tumors
Schreiber, K., Karrison, T. G., Wolf, S. P., Kiyotani, K., Steiner, M., Littmann, E. R., Pamer, E. G., Kammertoens, T., Schreiber, H. W., & Leisegang, M. (2019) · Cancer Immunology Research · doi:10.1158/2326-6066.cir-19-0567 · Cited by 21 · see citing works
What’s self got to do with it: Sources of heterogeneity among naive T cells
This, S., Rogers, D., Gauthier, È. M., Mandl, J. N., & Melichar, H. J. (2022) · Seminars in Immunology · doi:10.1016/j.smim.2022.101702 · Cited by 20 · see citing works
Dessalles, R., D'Orsogna, M. R., & Chou, T. (2018) · Journal of Statistical Physics · doi:10.1007/s10955-018-2128-4 · Cited by 20 · see citing works
Selected before selection: A case for inherent antigen bias in the T-cell receptor repertoire
Thomas, P. G., & Crawford, J. C. (2019) · Current Opinion in Systems Biology · doi:10.1016/j.coisb.2019.10.007 · Cited by 20 · see citing works
Smith, N. P., Ruiter, B., Virkud, Y. V., Tu, A. A., Monian, B., Moon, J. J., Love, J. C., & Shreffler, W. G. (2021) · JCI Insight · doi:10.1172/jci.insight.140028 · Cited by 20 · see citing works
NoisET: Noise Learning and Expansion Detection of T-Cell Receptors
Koraichi, M. B., Touzel, M. P., Mazzolini, A., Mora, T., & Walczak, A. M. (2022) · The Journal of Physical Chemistry A · doi:10.1021/acs.jpca.2c05002 · Cited by 22 · see citing works
The memory of the fatty acid system
Straub, R. H. (2020) · Progress in Lipid Research · doi:10.1016/j.plipres.2020.101049 · Cited by 20 · see citing works
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Lewkiewicz, S. M., Chuang, Y.-L., & Chou, T. (2019) · Bulletin of Mathematical Biology · doi:10.1007/s11538-019-00630-z · Cited by 16 · see citing works
Dessalles, R., Pan, Y., Xia, M., Maestrini, D., D'Orsogna, M. R., & Chou, T. (2022) · Frontiers in Immunology · doi:10.3389/fimmu.2021.735135 · Cited by 17 · see citing works
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Xu, S., Böttcher, L., & Chou, T. (2020) · Repository for Publications and Research Data (ETH Zurich) · doi:10.3929/ethz-b-000387958 · Cited by 17 · see citing works
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Gaevert, J. A., Duque, D. L., Lythe, G., Molina-Parı́s, C., & Thomas, P. G. (2021) · Viruses · doi:10.3390/v13091786 · Cited by 15 · see citing works
Self-citationChen, Z., John, J., & Wang, J. H. (2022) · Frontiers in Oncology · doi:10.3389/fonc.2022.995434 · Cited by 16 · see citing works
Bioengineering translational models of lymphoid tissues
Michaels, Y. S., Buchanan, C. F., Gjorevski, N., & Moisan, A. (2023) · Nature Reviews Bioengineering · doi:10.1038/s44222-023-00101-0 · Cited by 15 · see citing works
Vukmanović, S., & Sadrieh, N. K. (2017) · Critical Reviews in Toxicology · doi:10.1080/10408444.2017.1288025 · Cited by 14 · see citing works
Tolstykh, E. I., Дегтева, М. О., Vozilova, A. V., & Anspaugh, L. R. (2017) · Radiation and Environmental Biophysics · doi:10.1007/s00411-017-0712-7 · Cited by 14 · see citing works
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Nemunaitis, J. J., Stanbery, L., Willoughby, D., Bognar, E., Brun, S., Walter, A., Monk, B. J., Rocconi, R. P., Choucair, K., & Coleman, R. L. (2023) · Cancers · doi:10.3390/cancers15235616 · Cited by 13 · see citing works
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Desponds, J., Mayer, A., Mora, T., & Walczak, A. M. (2017) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/112755 · Cited by 13 · see citing works
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Bang, S., Xie, P., Lee, H., Wu, W., & Xing, E. P. (2019) · arXiv (Cornell University) · doi:10.48550/arxiv.1902.06918 · Cited by 13 · see citing works
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Toby, I. T., Levin, M. K., Salinas, E. A., Christley, S., Bhattacharya, S., Breden, F. J., Buntzman, A., Corrie, B., Fonner, J. M., Gupta, N. T., et al. (2016) · BMC Bioinformatics · doi:10.1186/s12859-016-1214-3 · Cited by 12 · see citing works
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Arnaud, M., Bobisse, S., Chiffelle, J., & Harari, A. (2021) · Frontiers in Immunology · doi:10.3389/fimmu.2021.701636 · Cited by 12 · see citing works
Immigration-induced phase transition in a regulated multispecies birth-death process
Xu, S., & Chou, T. (2018) · Journal of Physics A Mathematical and Theoretical · doi:10.1088/1751-8121/aadcb4 · Cited by 10 · see citing works
Changes in the Immune Cell Repertoire for the Treatment of Malignant Melanoma
Nakamura, K., & Okuyama, R. (2022) · International Journal of Molecular Sciences · doi:10.3390/ijms232112991 · Cited by 10 · see citing works
Mayer-Blackwell, K., Schattgen, S., Cohen-Lavi, L., Crawford, J. C., Souquette, A. H., Gaevert, J. A., Hertz, T., Thomas, P. G., Bradley, P. H., & Fiore-Gartland, A. (2020) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2020.12.24.424260 · Cited by 10 · see citing works
Structure modeling and specificity of peptide-MHC class I interactions using geometric deep learningPreprint
Aronson, A., Hochner, T., Cohen, T., & Schneidman‐Duhovny, D. (2022) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2022.12.15.520566 · Cited by 9 · see citing works
Transport Barriers Influence the Activation of Anti‐Tumor Immunity: A Systems Biology Analysis
Nikmaneshi, M. R., Baish, J. W., Zhou, H., Padera, T. P., & Munn, L. L. (2023) · Advanced Science · doi:10.1002/advs.202304076 · Cited by 9 · see citing works
CD3 downregulation identifies high-avidity human CD8 T cells
Clutton, G., Weideman, A. M., Mischell, M. A., Kallon, S., Conrad, S. Z., Shaw, F. R., Warren, J. A., Lin, L., Kuruc, J. D., Xu, Y., et al. (2023) · Clinical & Experimental Immunology · doi:10.1093/cei/uxad124 · Cited by 9 · see citing works
Population Dynamics of Immune Repertoires
Desponds, J., Mayer, A., Mora, T., & Walczak, A. M. (2021) · Springer eBooks · doi:10.1007/978-3-030-57204-4_12 · Cited by 9 · see citing works
Context-Aware Amino Acid Embedding Advances Analysis of TCR-Epitope InteractionsPreprint
Zhang, P., Bang, S., Cai, M., & Lee, H. (2023) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2023.04.12.536635 · Cited by 9 · see citing works
Mathematical Characterization of Private and Public Immune Receptor Sequences
Böttcher, L., Wald, S., & Chou, T. (2023) · Bulletin of Mathematical Biology · doi:10.1007/s11538-023-01190-z · Cited by 8 · see citing works
Analysis of Transcriptional Profiling of Immune Cells at the Single-Cell Level
Ferguson, A. A., & Chen, K. (2020) · Methods in molecular biology · doi:10.1007/978-1-0716-0266-9_4 · Cited by 8 · see citing works
T Cell Clonal Analysis Using Single-cell RNA Sequencing and Reference Maps
Andreatta, M., Gueguen, P., Borcherding, N. C., & Carmona, S. J. (2023) · BIO-PROTOCOL · doi:10.21769/bioprotoc.4735 · Cited by 8 · see citing works
Porcheddu, V., Lhomme, G., Giraudet, R., Correia, E., & Maillère, B. (2024) · Frontiers in Immunology · doi:10.3389/fimmu.2024.1345195 · Cited by 7 · see citing works
Niebuhr, M., Bahreini, F., Fähnrich, A., Bomholt, C., Bieber, K., Schmidt, E., Ibrahim, S. M., Hammers, C. M., & Kalies, K. (2022) · Frontiers in Immunology · doi:10.3389/fimmu.2022.1006941 · Cited by 7 · see citing works
Distinguishing between monozygotic twins' blood samples through immune repertoire sequencing
Meng, D., Zhou, P., Li, M., Xu, J., Lu, L., Guo, Y., Yu, C., Xu, Y., Xu, X., Chen, F., et al. (2023) · Forensic Science International Genetics · doi:10.1016/j.fsigen.2023.102828 · Cited by 7 · see citing works
T-cell virtuosity in ‘‘knowing thyself”
Acuto, O. (2024) · Frontiers in Immunology · doi:10.3389/fimmu.2024.1343575 · Cited by 7 · see citing works
Evaluation of the capacities of mouse TCR profiling from short read RNA-seq data
Bai, Y., Wang, D., Li, W., Huang, Y., Ye, X., Waite, J. C., Barry, T., Edelmann, K. H., Levenkova, N., Guo, C., et al. (2018) · PLoS ONE · doi:10.1371/journal.pone.0207020 · Cited by 7 · see citing works
A scaling law in CRISPR repertoire sizes arises from the avoidance of autoimmunity
Chen, H., Mayer, A., & Balasubramanian, V. (2022) · Current Biology · doi:10.1016/j.cub.2022.05.021 · Cited by 4 · see citing works
- Authors
- Lythe, G., Callard, R. E., Hoare, R. L., & Molina-París, C.
- Affiliations
- University of Leeds (GB)
- University College London (GB)
- Corresponding author
- Lythe, Grant
- Venue
- Journal of Theoretical Biology
- Publisher
- Elsevier BV
- Published
- 2016-01
- Volume
- 389
- Pages
- 214-224
- ISSN
- 0022-5193 (ISSN-L)
- PMC
- PMC4678146
- OpenAlex
- W2141312574
- Cited by
- 175
- References
- 134
- Citations by year
- 2026: 10 · 2025: 13 · 2024: 14 · 2023: 25 · 2022: 26 · 2021: 22 · 2020: 22 · 2019: 15 · 2018: 13 · 2017: 11 · 2016: 4
- FWCI
- 4.59
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Locations
- Journal of Theoretical Biology (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- White Rose Research Online (University of Leeds, The University of Sheffield, University of York) (acceptedVersion)
- UCL Discovery (University College London) (submittedVersion)
- Funders
- BBSRC Research Development Fellowship (BB/G023395/1)
- Topics
- Life Sciences › Immunology and Microbiology › Immunology › T-cell and B-cell Immunology
- Physical Sciences › Engineering › Biomedical Engineering › Artificial Immune Systems Applications
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Evolution and Genetic Dynamics
- Keywords
- T cell clonotypes, T cell receptor repertoire, thymic output, naive T cells
- MeSH terms
- Algorithms, Animals, Cell Division, Computer Simulation, Homeostasis, Humans, Immunologic Memory, Models, Theoretical, Receptors, Antigen, T-Cell, Stochastic Processes, T-Lymphocytes, Thymus Gland, Mice
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