Kevin C. Barry

3.3k total citations · 2 hit papers
18 papers, 1.5k citations indexed

About

Kevin C. Barry is a scholar working on Immunology, Molecular Biology and Oncology. According to data from OpenAlex, Kevin C. Barry has authored 18 papers receiving a total of 1.5k indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Immunology, 7 papers in Molecular Biology and 5 papers in Oncology. Recurrent topics in Kevin C. Barry's work include Immune Cell Function and Interaction (5 papers), Immunotherapy and Immune Responses (5 papers) and Neutrophil, Myeloperoxidase and Oxidative Mechanisms (3 papers). Kevin C. Barry is often cited by papers focused on Immune Cell Function and Interaction (5 papers), Immunotherapy and Immune Responses (5 papers) and Neutrophil, Myeloperoxidase and Oxidative Mechanisms (3 papers). Kevin C. Barry collaborates with scholars based in United States, Israel and Australia. Kevin C. Barry's co-authors include Matthew F. Krummel, Mark J. Smyth, Tobias Bald, Russell E. Vance, Mary F. Fontana, Zhao‐Qing Luo, Marko Spasić, Edward W. Roberts, Xihui Shen and Adil Daud and has published in prestigious journals such as Cell, Journal of Clinical Investigation and The EMBO Journal.

In The Last Decade

Kevin C. Barry

18 papers receiving 1.5k citations

Hit Papers

Unleashing Type-2 Dendritic Cells to Drive Protective Ant... 2019 2026 2021 2023 2019 2020 100 200 300 400

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Kevin C. Barry United States 15 911 582 581 231 160 18 1.5k
Norbert Hilf Germany 16 1.3k 1.4× 467 0.8× 1.0k 1.8× 54 0.2× 218 1.4× 31 1.9k
Roberto Carrió United States 18 1.1k 1.2× 340 0.6× 819 1.4× 45 0.2× 199 1.2× 27 1.8k
Ruzeen Patwa Australia 9 343 0.4× 238 0.4× 670 1.2× 74 0.3× 118 0.7× 13 1.5k
Andrea Itano United States 21 2.4k 2.6× 420 0.7× 640 1.1× 37 0.2× 171 1.1× 33 3.1k
Rachid Marhaba Germany 20 355 0.4× 358 0.6× 678 1.2× 100 0.4× 59 0.4× 24 1.4k
Purnima Dubey United States 20 583 0.6× 487 0.8× 556 1.0× 29 0.1× 147 0.9× 45 1.5k
Machie Sakuma Japan 13 1.1k 1.2× 208 0.4× 528 0.9× 45 0.2× 277 1.7× 16 1.6k
Joanne E. Davis Australia 17 527 0.6× 307 0.5× 408 0.7× 87 0.4× 225 1.4× 36 1.2k
Fazel Shokri Iran 21 611 0.7× 218 0.4× 406 0.7× 53 0.2× 145 0.9× 74 1.2k
Béatrice Bréart France 17 1.3k 1.4× 458 0.8× 604 1.0× 24 0.1× 157 1.0× 19 2.0k

Countries citing papers authored by Kevin C. Barry

Since Specialization
Citations

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

Fields of papers citing papers by Kevin C. Barry

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Kevin C. Barry. 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 Kevin C. Barry. The network helps show where Kevin C. Barry may publish in the future.

Co-authorship network of co-authors of Kevin C. Barry

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

All Works

18 of 18 papers shown
1.
Daniel, Sara K., Kevin M. Sullivan, Renske J.E. van den Bijgaart, et al.. (2024). Reversing immunosuppression in the tumor microenvironment of fibrolamellar carcinoma via PD-1 and IL-10 blockade. Scientific Reports. 14(1). 5109–5109. 5 indexed citations
2.
Dinh, Timothy A., Alan F. Utria, Kevin C. Barry, et al.. (2022). A framework for fibrolamellar carcinoma research and clinical trials. Nature Reviews Gastroenterology & Hepatology. 19(5). 328–342. 22 indexed citations
3.
Bickett, Thomas E., Michael W. Knitz, Laurel B. Darragh, et al.. (2021). FLT3L Release by Natural Killer Cells Enhances Response to Radioimmunotherapy in Preclinical Models of HNSCC. Clinical Cancer Research. 27(22). 6235–6249. 22 indexed citations
4.
Barry, Kevin C., et al.. (2021). The Natural Killer–Dendritic Cell Immune Axis in Anti-Cancer Immunity and Immunotherapy. Frontiers in Immunology. 11. 621254–621254. 51 indexed citations
5.
Minot, Samuel S., et al.. (2021). geneshot: gene-level metagenomics identifies genome islands associated with immunotherapy response. Genome biology. 22(1). 135–135. 14 indexed citations
6.
Bald, Tobias, Matthew F. Krummel, Mark J. Smyth, & Kevin C. Barry. (2020). The NK cell–cancer cycle: advances and new challenges in NK cell–based immunotherapies. Nature Immunology. 21(8). 835–847. 364 indexed citations breakdown →
8.
Binnewies, Mikhail, Adriana M. Mujal, Joshua L. Pollack, et al.. (2019). Unleashing Type-2 Dendritic Cells to Drive Protective Antitumor CD4+ T Cell Immunity. Cell. 177(3). 556–571.e16. 443 indexed citations breakdown →
9.
Barry, Kevin C. & Matthew F. Krummel. (2019). Abstract PR04: A natural killer–dendritic cell axis defines checkpoint therapy–responsive tumor microenvironments. Cancer Immunology Research. 7(2_Supplement). PR04–PR04. 3 indexed citations
10.
Qiu, Jiazhang, Christopher J. Nicolai, Jessica L. Counihan, et al.. (2017). Positive and Negative Regulation of the Master Metabolic Regulator mTORC1 by Two Families of Legionella pneumophila Effectors. Cell Reports. 21(8). 2031–2038. 49 indexed citations
11.
Barry, Kevin C., Nicholas T. Ingolia, & Russell E. Vance. (2017). Global analysis of gene expression reveals mRNA superinduction is required for the inducible immune response to a bacterial pathogen. eLife. 6. 35 indexed citations
12.
Ye, Jordan, Miranda L. Broz, Kevin C. Barry, et al.. (2016). Antitumor adaptive immunity remains intact following inhibition of autophagy and antimalarial treatment. Journal of Clinical Investigation. 126(12). 4417–4429. 62 indexed citations
13.
Fu, Zhu, et al.. (2014). Pseudomonas aeruginosa Quorum-Sensing Molecule Homoserine Lactone Modulates Inflammatory Signaling through PERK and eI-F2α. The Journal of Immunology. 193(3). 1459–1467. 25 indexed citations
14.
Barry, Kevin C., et al.. (2013). IL-1α Signaling Initiates the Inflammatory Response to Virulent Legionella pneumophila In Vivo. The Journal of Immunology. 190(12). 6329–6339. 106 indexed citations
15.
Barry, Kevin C., et al.. (2011). TheDrosophilaSTUbL protein Degringolade limits HES functions during embryogenesis. Development. 138(9). 1759–1769. 24 indexed citations
16.
Abed, Mona, Kevin C. Barry, T. Phippen, et al.. (2011). Degringolade, a SUMO‐targeted ubiquitin ligase, inhibits Hairy/Groucho‐mediated repression. The EMBO Journal. 30(7). 1289–1301. 56 indexed citations
17.
Fontana, Mary F., Simran Banga, Kevin C. Barry, et al.. (2011). Secreted Bacterial Effectors That Inhibit Host Protein Synthesis Are Critical for Induction of the Innate Immune Response to Virulent Legionella pneumophila. PLoS Pathogens. 7(2). e1001289–e1001289. 173 indexed citations
18.
Liu, Raymond, et al.. (2009). Wash functions downstream of Rho and links linear and branched actin nucleation factors. Development. 136(16). 2849–2860. 88 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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