Fiona A. Sharp

4.0k total citations · 1 hit paper
16 papers, 2.1k citations indexed

About

Fiona A. Sharp is a scholar working on Immunology, Molecular Biology and Oncology. According to data from OpenAlex, Fiona A. Sharp has authored 16 papers receiving a total of 2.1k indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Immunology, 8 papers in Molecular Biology and 6 papers in Oncology. Recurrent topics in Fiona A. Sharp's work include Immune Response and Inflammation (6 papers), Immunotherapy and Immune Responses (5 papers) and Inflammasome and immune disorders (5 papers). Fiona A. Sharp is often cited by papers focused on Immune Response and Inflammation (6 papers), Immunotherapy and Immune Responses (5 papers) and Inflammasome and immune disorders (5 papers). Fiona A. Sharp collaborates with scholars based in United States, Ireland and Switzerland. Fiona A. Sharp's co-authors include Ed C. Lavelle, James Harris, Emma M. Creagh, Jürg Tschopp, Tarek M. Fahmy, Michelle Hartman, Amy M. J. O’Shea, Hardy Kornfeld, Douglas T. Golenbock and Katherine A. Fitzgerald and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Journal of Biological Chemistry and Nature Immunology.

In The Last Decade

Fiona A. Sharp

15 papers receiving 2.1k citations

Hit Papers

Autophagy Controls IL-1β Secretion by Targeting Pro-IL-1β... 2011 2026 2016 2021 2011 200 400 600

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Fiona A. Sharp United States 11 1.1k 1.1k 519 213 209 16 2.1k
Limin Shang China 23 1.1k 1.0× 536 0.5× 295 0.6× 235 1.1× 205 1.0× 64 2.3k
Qiuhe Lu China 19 789 0.7× 1.7k 1.6× 453 0.9× 146 0.7× 94 0.4× 31 2.8k
Taiki Aoshi Japan 29 2.0k 1.9× 951 0.9× 472 0.9× 216 1.0× 148 0.7× 68 3.3k
Anna Sokolovska United States 18 1.2k 1.1× 1.3k 1.3× 378 0.7× 258 1.2× 410 2.0× 24 2.8k
Sven Burgdorf Germany 25 2.3k 2.1× 1.3k 1.2× 321 0.6× 390 1.8× 114 0.5× 42 3.6k
Wulf Schneider‐Brachert Germany 33 830 0.8× 1.3k 1.2× 378 0.7× 228 1.1× 123 0.6× 98 3.4k
Folkert Steinhagen Germany 18 1.3k 1.2× 717 0.7× 420 0.8× 239 1.1× 141 0.7× 32 2.2k
Étienne Meunier France 25 1.1k 1.0× 1.8k 1.7× 382 0.7× 98 0.5× 113 0.5× 41 2.7k
Piergiuseppe De Berardinis Italy 26 709 0.7× 754 0.7× 208 0.4× 136 0.6× 135 0.6× 70 2.2k
Adi Idris Australia 25 1.1k 1.0× 1.5k 1.4× 401 0.8× 255 1.2× 88 0.4× 78 2.6k

Countries citing papers authored by Fiona A. Sharp

Since Specialization
Citations

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

Fields of papers citing papers by Fiona A. Sharp

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Fiona A. Sharp

This figure shows the co-authorship network connecting the top 25 collaborators of Fiona A. Sharp. A scholar is included among the top collaborators of Fiona A. Sharp 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 Fiona A. Sharp. Fiona A. Sharp 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.
Muñoz‐Wolf, Natalia, Ross W. Ward, Claire H. Hearnden, et al.. (2023). Non-canonical inflammasome activation mediates the adjuvanticity of nanoparticles. Cell Reports Medicine. 4(1). 100899–100899. 22 indexed citations
2.
Lin, Sharon, Leila J. Williams, Hugh Gannon, et al.. (2022). 255 ExPRESSTM: An accelerated process for the manufacture of KSQ-001, a CRISPR/Cas9-edited eTILTM product. Regular and Young Investigator Award Abstracts. A270–A270. 1 indexed citations
3.
Muñoz‐Wolf, Natalia, Ross W. Ward, Claire H. Hearnden, et al.. (2022). Non‐Canonical Inflammasome Activation Mediates the Adjuvanticity of Nanoparticles. SSRN Electronic Journal. 6 indexed citations
4.
Wong, Karrie, Leila J. Williams, Nicholas Constant, et al.. (2022). 297 Manufacture of KSQ-001, a CRISPR/Cas9-engineered TIL (eTIL) therapy, for the treatment of head and neck squamous cell carcinoma. Regular and Young Investigator Award Abstracts. A312–A312.
5.
Wang, Hui Qin, Iain J. Mulford, Fiona A. Sharp, et al.. (2021). Inhibition of MDM2 Promotes Antitumor Responses in p53 Wild-Type Cancer Cells through Their Interaction with the Immune and Stromal Microenvironment. Cancer Research. 81(11). 3079–3091. 43 indexed citations
6.
Sabatos-Peyton, Catherine, Tyler A. Longmire, Nidhi Patel, et al.. (2020). 439 Dual modes of action for anti-TIM-3 antibody MBG453 in myelodysplastic syndromes (MDS) and acute myeloid leukemia (AML): preclinical evidence for immune-mediated and anti-leukemic activity. Regular and Young Investigator Award Abstracts. A267.1–A267. 7 indexed citations
7.
Oleszycka, Ewa, Fiona A. Sharp, Natalia Muñoz‐Wolf, et al.. (2018). The vaccine adjuvant alum promotes IL‐10 production that suppresses Th1 responses. European Journal of Immunology. 48(4). 705–715. 75 indexed citations
8.
Wang, Hui Qin, Jinsheng Liang, Iain J. Mulford, et al.. (2018). Abstract 5560: PD-1/PD-L1 blockade enhances MDM2 inhibitor activity in p53 wild-type cancers. Cancer Research. 78(13_Supplement). 5560–5560. 3 indexed citations
9.
Fadel, Tarek R., Fiona A. Sharp, Nalini Vudattu, et al.. (2014). A carbon nanotube–polymer composite for T-cell therapy. Nature Nanotechnology. 9(8). 639–647. 200 indexed citations
10.
Hanlon, Douglas, Sandeep Saluja, Fiona A. Sharp, et al.. (2014). Targeting human dendritic cells via DEC-205 using PLGA nanoparticles leads to enhanced cross-presentation of a melanoma-associated antigen. International Journal of Nanomedicine. 9. 5231–5231. 82 indexed citations
11.
Mori, Andrés, Ewa Oleszycka, Fiona A. Sharp, et al.. (2012). The vaccine adjuvant alum inhibits IL‐12 by promoting PI3 kinase signaling while chitosan does not inhibit IL‐12 and enhances Th1 and Th17 responses. European Journal of Immunology. 42(10). 2709–2719. 115 indexed citations
12.
Harris, James, Michelle Hartman, Amy M. J. O’Shea, et al.. (2011). Autophagy Controls IL-1β Secretion by Targeting Pro-IL-1β for Degradation. Journal of Biological Chemistry. 286(11). 9587–9597. 664 indexed citations breakdown →
13.
Demento, Stacey L., Alyssa Siefert, Arunima Bandyopadhyay, Fiona A. Sharp, & Tarek M. Fahmy. (2011). Pathogen-associated molecular patterns on biomaterials: a paradigm for engineering new vaccines. Trends in biotechnology. 29(6). 294–306. 137 indexed citations
14.
Harris, James, Fiona A. Sharp, & Ed C. Lavelle. (2010). The role of inflammasomes in the immunostimulatory effects of particulate vaccine adjuvants. European Journal of Immunology. 40(3). 634–638. 41 indexed citations
15.
Sharp, Fiona A., Darren Ruane, Benjamin Claass, et al.. (2009). Uptake of particulate vaccine adjuvants by dendritic cells activates the NALP3 inflammasome. Proceedings of the National Academy of Sciences. 106(3). 870–875. 437 indexed citations
16.
Khan, Naseema N., Sara C. McGrath, Fiona A. Sharp, et al.. (2006). Virulence factors of Yersinia pestis are overcome by a strong lipopolysaccharide response. Nature Immunology. 7(10). 1066–1073. 314 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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