Daryan A. Kaveh

554 total citations
16 papers, 454 citations indexed

About

Daryan A. Kaveh is a scholar working on Immunology, Infectious Diseases and Epidemiology. According to data from OpenAlex, Daryan A. Kaveh has authored 16 papers receiving a total of 454 indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Immunology, 11 papers in Infectious Diseases and 4 papers in Epidemiology. Recurrent topics in Daryan A. Kaveh's work include Tuberculosis Research and Epidemiology (11 papers), Immune responses and vaccinations (9 papers) and T-cell and B-cell Immunology (4 papers). Daryan A. Kaveh is often cited by papers focused on Tuberculosis Research and Epidemiology (11 papers), Immune responses and vaccinations (9 papers) and T-cell and B-cell Immunology (4 papers). Daryan A. Kaveh collaborates with scholars based in United Kingdom, Canada and Denmark. Daryan A. Kaveh's co-authors include Philip J. Hogarth, M. Carmen García‐Pelayo, Véronique Bachy, R. Glyn Hewinson, Elihú Aranday-Cortés, Adam O. Whelan, Naomi Bull, Elena Stylianou, Helen McShane and H. M. Vordermeier and has published in prestigious journals such as PLoS ONE, Scientific Reports and Vaccine.

In The Last Decade

Daryan A. Kaveh

16 papers receiving 451 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Daryan A. Kaveh United Kingdom 11 293 290 159 99 22 16 454
Wy Ching Ng Australia 13 210 0.7× 132 0.5× 179 1.1× 93 0.9× 12 0.5× 20 427
Siamak Haddadi Canada 10 439 1.5× 264 0.9× 132 0.8× 110 1.1× 22 1.0× 13 654
Levelle D. Harris United States 8 452 1.5× 292 1.0× 243 1.5× 115 1.2× 24 1.1× 9 838
Niels Peter Hell Knudsen Denmark 8 297 1.0× 273 0.9× 174 1.1× 106 1.1× 11 0.5× 13 478
Sophia M. Vrba United States 6 130 0.4× 160 0.6× 71 0.4× 118 1.2× 20 0.9× 10 354
Mary Réquena France 12 228 0.8× 194 0.7× 105 0.7× 66 0.7× 9 0.4× 18 504
D.L. Keen New Zealand 8 226 0.8× 340 1.2× 252 1.6× 82 0.8× 8 0.4× 10 416
Natalie E. R. Beveridge United Kingdom 7 354 1.2× 416 1.4× 221 1.4× 107 1.1× 27 1.2× 9 544
Laurence Handt United States 6 170 0.6× 79 0.3× 110 0.7× 108 1.1× 15 0.7× 7 358
Natasha Dubois Cauwelaert United States 10 202 0.7× 142 0.5× 153 1.0× 106 1.1× 16 0.7× 14 403

Countries citing papers authored by Daryan A. Kaveh

Since Specialization
Citations

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

Fields of papers citing papers by Daryan A. Kaveh

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Daryan A. Kaveh. 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 Daryan A. Kaveh. The network helps show where Daryan A. Kaveh may publish in the future.

Co-authorship network of co-authors of Daryan A. Kaveh

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

All Works

16 of 16 papers shown
1.
Howells, Laurence, Daryan A. Kaveh, Sevil Erdenliğ Gürbi̇lek, et al.. (2022). The Tip of Brucella O-Polysaccharide Is a Potent Epitope in Response to Brucellosis Infection and Enables Short Synthetic Antigens to Be Superior Diagnostic Reagents. Microorganisms. 10(4). 708–708. 6 indexed citations
2.
Khatri, Bhagwati, et al.. (2021). Efficacy and immunogenicity of different BCG doses in BALB/c and CB6F1 mice when challenged with H37Rv or Beijing HN878. Scientific Reports. 11(1). 23308–23308. 7 indexed citations
3.
Kaveh, Daryan A., M. Carmen García‐Pelayo, Naomi Bull, et al.. (2020). Airway delivery of both a BCG prime and adenoviral boost drives CD4 and CD8 T cells into the lung tissue parenchyma. Scientific Reports. 10(1). 18703–18703. 4 indexed citations
4.
Bull, Naomi, Elena Stylianou, Daryan A. Kaveh, et al.. (2018). Enhanced protection conferred by mucosal BCG vaccination associates with presence of antigen-specific lung tissue-resident PD-1+ KLRG1− CD4+ T cells. Mucosal Immunology. 12(2). 555–564. 67 indexed citations
5.
Bull, Naomi, Daryan A. Kaveh, M. Carmen García‐Pelayo, et al.. (2018). Induction and maintenance of a phenotypically heterogeneous lung tissue-resident CD4+ T cell population following BCG immunisation. Vaccine. 36(37). 5625–5635. 28 indexed citations
6.
Edwards, Jane C., Helen Everett, Miriam Pedrera, et al.. (2017). CD1− and CD1+ porcine blood dendritic cells are enriched for the orthologues of the two major mammalian conventional subsets. Scientific Reports. 7(1). 40942–40942. 23 indexed citations
7.
Kaveh, Daryan A., et al.. (2016). Parenteral adenoviral boost enhances BCG induced protection, but not long term survival in a murine model of bovine TB. Vaccine. 34(34). 4003–4011. 7 indexed citations
8.
Hogarth, Philip J., et al.. (2015). Phenotypic characterization of bovine memory cells responding to mycobacteria in IFNγ enzyme linked immunospot assays. Vaccine. 33(51). 7276–7282. 13 indexed citations
9.
García‐Pelayo, M. Carmen, Véronique Bachy, Daryan A. Kaveh, & Philip J. Hogarth. (2014). BALB/c mice display more enhanced BCG vaccine induced Th1 and Th17 response than C57BL/6 mice but have equivalent protection. Tuberculosis. 95(1). 48–53. 47 indexed citations
10.
Kaveh, Daryan A., M. Carmen García‐Pelayo, & Philip J. Hogarth. (2014). Persistent BCG bacilli perpetuate CD4 T effector memory and optimal protection against tuberculosis. Vaccine. 32(51). 6911–6918. 56 indexed citations
11.
Jones, Gareth J., Bhagwati Khatri, M. Carmen García‐Pelayo, et al.. (2013). Development of an Unbiased Antigen-Mining Approach To Identify Novel Vaccine Antigens and Diagnostic Reagents for Bovine Tuberculosis. Clinical and Vaccine Immunology. 20(11). 1675–1682. 8 indexed citations
12.
Kaveh, Daryan A., Adam O. Whelan, & Philip J. Hogarth. (2012). The Duration of Antigen-Stimulation Significantly Alters the Diversity of Multifunctional CD4 T Cells Measured by Intracellular Cytokine Staining. PLoS ONE. 7(6). e38926–e38926. 20 indexed citations
13.
Aranday-Cortés, Elihú, Philip J. Hogarth, Daryan A. Kaveh, et al.. (2012). Transcriptional Profiling of Disease-Induced Host Responses in Bovine Tuberculosis and the Identification of Potential Diagnostic Biomarkers. PLoS ONE. 7(2). e30626–e30626. 52 indexed citations
14.
Kaveh, Daryan A., Véronique Bachy, R. Glyn Hewinson, & Philip J. Hogarth. (2011). Systemic BCG Immunization Induces Persistent Lung Mucosal Multifunctional CD4 TEM Cells which Expand Following Virulent Mycobacterial Challenge. PLoS ONE. 6(6). e21566–e21566. 62 indexed citations
15.
Aranday-Cortés, Elihú, Daryan A. Kaveh, Javier Nuñéz-García, Philip J. Hogarth, & H. Martin Vordermeier. (2010). Mycobacterium bovis-BCG Vaccination Induces Specific Pulmonary Transcriptome Biosignatures in Mice. PLoS ONE. 5(6). e11319–e11319. 36 indexed citations
16.
Vordermeier, H. Martin, Gillian S. Dean, Ida Rosenkrands, et al.. (2009). Adjuvants Induce Distinct Immunological Phenotypes in a Bovine Tuberculosis Vaccine Model. Clinical and Vaccine Immunology. 16(10). 1443–1448. 18 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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