David Bending

1.9k total citations
32 papers, 1.3k citations indexed

About

David Bending is a scholar working on Immunology, Oncology and Molecular Biology. According to data from OpenAlex, David Bending has authored 32 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 25 papers in Immunology, 8 papers in Oncology and 6 papers in Molecular Biology. Recurrent topics in David Bending's work include Immune Cell Function and Interaction (16 papers), T-cell and B-cell Immunology (13 papers) and CAR-T cell therapy research (7 papers). David Bending is often cited by papers focused on Immune Cell Function and Interaction (16 papers), T-cell and B-cell Immunology (13 papers) and CAR-T cell therapy research (7 papers). David Bending collaborates with scholars based in United Kingdom, United States and Japan. David Bending's co-authors include Anne Cooke, Brigitta Stockinger, Jenny M. Phillips, Hugo De La Peña, Catherine Uyttenhove, Marc Veldhoen, Lucy R. Wedderburn, Anne M. Pesenacker, Kiran Nistala and Masahiro Ono and has published in prestigious journals such as Journal of Clinical Investigation, The Journal of Cell Biology and The EMBO Journal.

In The Last Decade

David Bending

29 papers receiving 1.3k citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
David Bending United Kingdom	16	921	242	209	180	91	32	1.3k
Yufeng Peng United States	13	767 0.8×	250 1.0×	163 0.8×	144 0.8×	102 1.1×	30	1.2k
Huie Jing United States	18	1.2k 1.3×	255 1.1×	390 1.9×	185 1.0×	94 1.0×	21	1.7k
Husein Hadeiba United States	12	1.2k 1.3×	292 1.2×	174 0.8×	192 1.1×	99 1.1×	17	1.7k
Katrina K. Hoyer United States	17	763 0.8×	289 1.2×	73 0.3×	171 0.9×	60 0.7×	36	1.2k
Kim Waggie United States	10	865 0.9×	229 0.9×	167 0.8×	196 1.1×	165 1.8×	12	1.5k
Stacey N. Harbour Australia	16	735 0.8×	343 1.4×	159 0.8×	189 1.1×	253 2.8×	20	1.3k
Marion Salou France	17	1.2k 1.3×	294 1.2×	132 0.6×	246 1.4×	66 0.7×	30	1.6k
Carole Guillonneau France	29	1.4k 1.6×	316 1.3×	157 0.8×	326 1.8×	129 1.4×	58	1.9k
Hans‐Gerd Pauels Germany	13	548 0.6×	264 1.1×	272 1.3×	150 0.8×	114 1.3×	26	1.2k
Laura Campisi United States	11	754 0.8×	276 1.1×	123 0.6×	158 0.9×	46 0.5×	13	1.1k

Countries citing papers authored by David Bending

Since Specialization

Citations

This map shows the geographic impact of David Bending'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 David Bending with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites David Bending more than expected).

Fields of papers citing papers by David Bending

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by David Bending. 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 David Bending. The network helps show where David Bending may publish in the future.

Co-authorship network of co-authors of David Bending

This figure shows the co-authorship network connecting the top 25 collaborators of David Bending. A scholar is included among the top collaborators of David Bending 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 David Bending. David Bending is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

Pike, Jeremy A., et al.. (2025). Remote Force Modulation of the T‐Cell Receptor Reveals an NFAT‐Threshold for CD4 ⁺ T‐Cell Activation. European Journal of Immunology. 55(6). e51716–e51716.

Sheriff, Lozan, et al.. (2025). Interferon-γ and IL-27 positively regulate type 1 regulatory T cell development during adaptive tolerance. iScience. 28(5). 112308–112308.

Sheriff, Lozan, et al.. (2024). Lag3 and PD-1 pathways preferentially regulate NFAT-dependent TCR signalling programmes during early CD4+ T cell activation. PubMed. 5(1). ltaf015–ltaf015. 1 indexed citations

Copland, Alastair, Elizabeth Jinks, Nancy Gudgeon, et al.. (2024). Salmonella cancer therapy metabolically disrupts tumours at the collateral cost of T cell immunity. EMBO Molecular Medicine. 16(12). 3057–3088. 6 indexed citations

Bending, David, et al.. (2023). T-cell response to checkpoint blockade immunotherapies: from fundamental mechanisms to treatment signatures. Essays in Biochemistry. 67(6). 967–977. 1 indexed citations

Quintana, Juan F., Matthew C. Sinton, Lalit Kumar Dubey, et al.. (2023). The murine meninges acquire lymphoid tissue properties and harbour autoreactive B cells during chronic Trypanosoma brucei infection. PLoS Biology. 21(11). e3002389–e3002389. 8 indexed citations

Bending, David & Julie Zikherman. (2023). Nr4a nuclear receptors: markers and modulators of antigen receptor signaling. Current Opinion in Immunology. 81. 102285–102285. 13 indexed citations

Drummond, Rebecca A., Jigar V. Desai, Emily Ricotta, et al.. (2022). Long-term antibiotic exposure promotes mortality after systemic fungal infection by driving lymphocyte dysfunction and systemic escape of commensal bacteria. Cell Host & Microbe. 30(7). 1020–1033.e6. 75 indexed citations

Sheriff, Lozan & David Bending. (2022). Flow cytometric analysis of CD4+ T cell reactivation following anti-PD1 immunotherapy in a transgenic mouse model. STAR Protocols. 3(1). 101161–101161. 1 indexed citations

10.

Flores‐Langarica, Adriana, et al.. (2021). Antigen and checkpoint receptor engagement recalibrates T cell receptor signal strength. Immunity. 54(11). 2481–2496.e6. 38 indexed citations

11.

Ono, Masahiro, et al.. (2021). Application of dual Nr4a1-GFP Nr4a3-Tocky reporter mice to study T cell receptor signaling by flow cytometry. STAR Protocols. 2(1). 100284–100284. 5 indexed citations

12.

Yam‐Puc, Juan Carlos, Masahiro Ono, Kai‐Michael Toellner, et al.. (2020). Nr4a1 and Nr4a3 Reporter Mice Are Differentially Sensitive to T Cell Receptor Signal Strength and Duration. Cell Reports. 33(5). 108328–108328. 58 indexed citations

13.

Bending, David, et al.. (2018). A temporally dynamic Foxp3 autoregulatory transcriptional circuit controls the effector Treg programme. The EMBO Journal. 37(16). 34 indexed citations

14.

Copland, Alastair & David Bending. (2018). Foxp3 Molecular Dynamics in Treg in Juvenile Idiopathic Arthritis. Frontiers in Immunology. 9. 2273–2273. 10 indexed citations

15.

Rosser, Elizabeth C., et al.. (2018). Innate Lymphoid Cells and T Cells Contribute to the Interleukin‐17A Signature Detected in the Synovial Fluid of Patients With Juvenile Idiopathic Arthritis. Arthritis & Rheumatology. 71(3). 460–467. 17 indexed citations

16.

Piper, Christopher, David Bending, Hemlata Varsani, et al.. (2014). Regulatory B cell Il-10 production is diminished in juvenile dermatomyositis. Pediatric Rheumatology. 12(S1). 1 indexed citations

17.

Morrison, Peter J., David Bending, Lynette A. Fouser, et al.. (2013). Th17-cell plasticity in Helicobacter hepaticus–induced intestinal inflammation. Mucosal Immunology. 6(6). 1143–1156. 85 indexed citations

18.

Wadhwa, Meenu, Paula Dilger, David Bending, et al.. (2012). The 1st International standard for transforming growth factor-β3 (TGF-β3). Journal of Immunological Methods. 380(1-2). 1–9. 2 indexed citations

19.

Bending, David, Paola Zaccone, & Anne Cooke. (2012). Inflammation and type one diabetes. International Immunology. 24(6). 339–346. 53 indexed citations

20.

Bending, David, Hugo De La Peña, Marc Veldhoen, et al.. (2009). Highly purified Th17 cells from BDC2.5NOD mice convert into Th1-like cells in NOD/SCID recipient mice. Journal of Clinical Investigation. 119(3). 565–572. 430 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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