Grant Lythe

1.9k total citations
71 papers, 1.2k citations indexed

About

Grant Lythe is a scholar working on Immunology, Molecular Biology and Statistical and Nonlinear Physics. According to data from OpenAlex, Grant Lythe has authored 71 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 25 papers in Immunology, 19 papers in Molecular Biology and 14 papers in Statistical and Nonlinear Physics. Recurrent topics in Grant Lythe's work include T-cell and B-cell Immunology (22 papers), Immune Cell Function and Interaction (17 papers) and Theoretical and Computational Physics (9 papers). Grant Lythe is often cited by papers focused on T-cell and B-cell Immunology (22 papers), Immune Cell Function and Interaction (17 papers) and Theoretical and Computational Physics (9 papers). Grant Lythe collaborates with scholars based in United Kingdom, United States and Spain. Grant Lythe's co-authors include Carmen Molina-Parı́s, Kevin Burrage, Salman Habib, Kalvis M. Jansons, I.J. Lenane, Robin E. Callard, Joseph M. Reynolds, Mario Castro, Vassilios Kovanis and Thomas Erneux and has published in prestigious journals such as Physical Review Letters, Nature Communications and The Journal of Chemical Physics.

In The Last Decade

Grant Lythe

68 papers receiving 1.1k citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Grant Lythe United Kingdom 20 432 278 201 144 117 71 1.2k
Hiroyuki Nagashima Japan 25 583 1.3× 286 1.0× 260 1.3× 182 1.3× 129 1.1× 113 1.9k
Robert S. Sinkovits United States 22 206 0.5× 517 1.9× 214 1.1× 59 0.4× 93 0.8× 67 1.8k
Michal Or‐Guil Germany 18 157 0.4× 249 0.9× 317 1.6× 95 0.7× 450 3.8× 39 995
Holger Hennig Germany 28 206 0.5× 439 1.6× 177 0.9× 284 2.0× 35 0.3× 88 2.7k
Naoko Nakagawa Japan 26 655 1.5× 526 1.9× 530 2.6× 468 3.3× 317 2.7× 91 2.6k
Tomasz Lipniacki Poland 27 604 1.4× 1.5k 5.4× 94 0.5× 313 2.2× 38 0.3× 88 2.6k
Carlo Danieli South Korea 15 1.8k 4.2× 607 2.2× 288 1.4× 201 1.4× 49 0.4× 26 2.7k
Štefan Bálint Romania 17 265 0.6× 351 1.3× 42 0.2× 91 0.6× 35 0.3× 86 1.0k
F. Hayot United States 23 219 0.5× 541 1.9× 170 0.8× 56 0.4× 150 1.3× 93 1.7k
Andreas Mayer Germany 26 139 0.3× 196 0.7× 250 1.2× 33 0.2× 101 0.9× 141 2.2k

Countries citing papers authored by Grant Lythe

Since Specialization
Citations

This map shows the geographic impact of Grant Lythe's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Grant Lythe with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Grant Lythe more than expected).

Fields of papers citing papers by Grant Lythe

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Grant Lythe. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Grant Lythe. The network helps show where Grant Lythe may publish in the future.

Co-authorship network of co-authors of Grant Lythe

This figure shows the co-authorship network connecting the top 25 collaborators of Grant Lythe. A scholar is included among the top collaborators of Grant Lythe based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Grant Lythe. Grant Lythe is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Wigerblad, Gustaf, Sumanta Ray, Thomas Finnie, et al.. (2025). A mathematical framework for human neutrophil state transitions inferred from single-cell RNA sequence data. Frontiers in Immunology. 16. 1654015–1654015.
2.
Lythe, Grant, et al.. (2025). Mechanistic within-host mathematical model of inhalational anthrax. PLoS Computational Biology. 21(9). e1013439–e1013439.
3.
López‐García, Martín, et al.. (2022). Counting generations in birth and death processes with competing Erlang and exponential waiting times. Scientific Reports. 12(1). 11289–11289. 4 indexed citations
4.
Wilmes, Stephan, Jonathan Martínez‐Fábregas, Maximillian Hafer, et al.. (2021). Competitive binding of STATs to receptor phospho-Tyr motifs accounts for altered cytokine responses. eLife. 10. 17 indexed citations
5.
López‐García, Martín, et al.. (2021). A Stochastic Intracellular Model of Anthrax Infection With Spore Germination Heterogeneity. Frontiers in Immunology. 12. 688257–688257. 6 indexed citations
6.
Liao, Laura E., Sophie J. Smither, Simon A. Weller, et al.. (2020). Quantification of Ebola virus replication kinetics in vitro. PLoS Computational Biology. 16(11). e1008375–e1008375. 10 indexed citations
7.
López‐García, Martín, et al.. (2019). Fate of a Naive T Cell: A Stochastic Journey. Frontiers in Immunology. 10. 194–194. 8 indexed citations
8.
López‐García, Martín, et al.. (2018). A Novel Stochastic Multi-Scale Model of Francisella tularensis Infection to Predict Risk of Infection in a Laboratory. Frontiers in Microbiology. 9. 1165–1165. 8 indexed citations
9.
Blanco, Raquel, Celia Alda-Catalinas, Clara L. Oeste, et al.. (2018). A window of opportunity for cooperativity in the T Cell Receptor. Nature Communications. 9(1). 2618–2618. 22 indexed citations
10.
Castro, Mario, Grant Lythe, Carmen Molina-Parı́s, & Ruy M. Ribeiro. (2016). Mathematics in modern immunology. Interface Focus. 6(2). 20150093–20150093. 20 indexed citations
11.
Donovan, Graham M. & Grant Lythe. (2016). T cell and reticular network co-dependence in HIV infection. Journal of Theoretical Biology. 395. 211–220. 9 indexed citations
12.
Laws, Thomas R., et al.. (2014). Modeling early events in Francisella tularensis pathogenesis. Frontiers in Cellular and Infection Microbiology. 4. 169–169. 14 indexed citations
13.
Castro, Mario, et al.. (2014). Receptor Pre-Clustering and T cell Responses: Insights into Molecular Mechanisms. Frontiers in Immunology. 5. 132–132. 19 indexed citations
14.
Stritesky, Gretta L., et al.. (2014). From pre-DP, post-DP, SP4, and SP8 Thymocyte Cell Counts to a Dynamical Model of Cortical and Medullary Selection. Frontiers in Immunology. 5. 19–19. 27 indexed citations
15.
Reynolds, Joseph M., Inês F. Amado, António A. Freitas, Grant Lythe, & Carmen Molina-Parı́s. (2014). A mathematical perspective on CD4+ T cell quorum-sensing. Journal of Theoretical Biology. 347. 160–175. 5 indexed citations
16.
Reynolds, Joseph M., Mark Coles, Grant Lythe, & Carmen Molina-Parı́s. (2013). Mathematical Model of Naive T Cell Division and Survival IL-7 Thresholds. Frontiers in Immunology. 4. 434–434. 18 indexed citations
17.
Almeida, Afonso R. M., Inês F. Amado, Joseph M. Reynolds, et al.. (2012). Quorum-Sensing in CD4+ T Cell Homeostasis: A Hypothesis and a Model. Frontiers in Immunology. 3. 125–125. 73 indexed citations
18.
Lythe, Grant, et al.. (2010). Stochastic competitive exclusion in the maintenance of the naïve T cell repertoire. Journal of Theoretical Biology. 265(3). 396–410. 18 indexed citations
19.
Lythe, Grant, et al.. (2010). The limiting conditional probability distribution in a stochastic model of T cell repertoire maintenance. Mathematical Biosciences. 224(2). 74–86. 14 indexed citations
20.
Lythe, Grant. (1968). Doctor or Social Worker?. BMJ. 3(5615). 435.4–435. 6 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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