Kim L. O’Neill

5.7k total citations · 1 hit paper
129 papers, 4.4k citations indexed

About

Kim L. O’Neill is a scholar working on Molecular Biology, Oncology and Epidemiology. According to data from OpenAlex, Kim L. O’Neill has authored 129 papers receiving a total of 4.4k indexed citations (citations by other indexed papers that have themselves been cited), including 55 papers in Molecular Biology, 38 papers in Oncology and 23 papers in Epidemiology. Recurrent topics in Kim L. O’Neill's work include Chronic Lymphocytic Leukemia Research (16 papers), Carcinogens and Genotoxicity Assessment (16 papers) and Neuroendocrine Tumor Research Advances (12 papers). Kim L. O’Neill is often cited by papers focused on Chronic Lymphocytic Leukemia Research (16 papers), Carcinogens and Genotoxicity Assessment (16 papers) and Neuroendocrine Tumor Research Advances (12 papers). Kim L. O’Neill collaborates with scholars based in United States, United Kingdom and Egypt. Kim L. O’Neill's co-authors include Daryl W. Fairbairn, Peggy L. Olive, Richard A. Robison, Michelle H. Townsend, Byron K. Murray, Frederick L. Hall, M Torres, Andrew Garrett, David P. Tomer and Gajendra Shrestha and has published in prestigious journals such as Journal of Clinical Investigation, The Journal of Immunology and PLoS ONE.

In The Last Decade

Kim L. O’Neill

127 papers receiving 4.3k citations

Hit Papers

The comet assay: a comprehensive review 1995 2026 2005 2015 1995 400 800 1.2k

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Kim L. O’Neill United States 33 1.7k 1.2k 650 609 546 129 4.4k
Chien‐Chih Chiu Taiwan 41 2.8k 1.6× 806 0.7× 563 0.9× 273 0.4× 321 0.6× 199 5.2k
Masuo Kondoh Japan 40 2.1k 1.3× 357 0.3× 540 0.8× 524 0.9× 361 0.7× 212 5.6k
Tomáš Eckschlager Czechia 37 3.0k 1.8× 566 0.5× 1.0k 1.6× 779 1.3× 216 0.4× 158 5.9k
Makoto Umeda Japan 39 1.7k 1.0× 1.3k 1.1× 713 1.1× 339 0.6× 432 0.8× 175 4.1k
Yu‐Ying He United States 44 2.9k 1.7× 892 0.8× 723 1.1× 170 0.3× 351 0.6× 118 5.6k
Wenlin Huang China 46 3.9k 2.3× 1.7k 1.4× 975 1.5× 265 0.4× 638 1.2× 168 6.9k
Pablo Steinberg Germany 32 1.6k 0.9× 666 0.6× 434 0.7× 345 0.6× 427 0.8× 151 3.8k
Bernd Epe Germany 44 4.2k 2.5× 1.4k 1.2× 594 0.9× 347 0.6× 288 0.5× 167 6.2k
Shuang Liu China 41 3.2k 1.9× 831 0.7× 882 1.4× 282 0.5× 778 1.4× 242 6.5k
Jinhua Wang China 48 4.1k 2.5× 2.3k 2.0× 876 1.3× 457 0.8× 434 0.8× 185 7.4k

Countries citing papers authored by Kim L. O’Neill

Since Specialization
Citations

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

Fields of papers citing papers by Kim L. O’Neill

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Kim L. O’Neill. 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 Kim L. O’Neill. The network helps show where Kim L. O’Neill may publish in the future.

Co-authorship network of co-authors of Kim L. O’Neill

This figure shows the co-authorship network connecting the top 25 collaborators of Kim L. O’Neill. A scholar is included among the top collaborators of Kim L. O’Neill 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 Kim L. O’Neill. Kim L. O’Neill 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.
O’Neill, Kim L., et al.. (2025). Chimeric autoantibody receptor T cells specifically eliminate Graves’ Disease autoreactive B cells. Frontiers in Immunology. 16. 1562662–1562662. 1 indexed citations
2.
Weber, K. Scott, et al.. (2023). Characterizing the Interplay of Lymphocytes in Graves’ Disease. International Journal of Molecular Sciences. 24(7). 6835–6835. 14 indexed citations
4.
Townsend, Michelle H., et al.. (2021). Overexpression and surface localization of HPRT in prostate cancer provides a potential target for cancer specific antibody mediated cellular cytotoxicity. Experimental Cell Research. 403(1). 112567–112567. 8 indexed citations
5.
Shrestha, Gajendra, Michelle H. Townsend, Bradford K. Berges, et al.. (2020). Novel monoclonal antibodies against thymidine kinase 1 and their potential use for the immunotargeting of lung, breast and colon cancer cells. Cancer Cell International. 20(1). 127–127. 8 indexed citations
6.
Townsend, Michelle H., Richard A. Robison, & Kim L. O’Neill. (2018). A review of HPRT and its emerging role in cancer. Medical Oncology. 35(6). 89–89. 57 indexed citations
7.
Townsend, Michelle H., et al.. (2017). Abstract 1949: Salvage pathway enzyme HPRT as a molecular marker for Burkitt’s Lymphoma. Cancer Research. 77(13_Supplement). 1949–1949. 1 indexed citations
8.
Townsend, Michelle H., et al.. (2017). Non-small-cell lung cancer cell lines A549 and NCI-H460 express hypoxanthine guanine phosphoribosyltransferase on the plasma membrane. OncoTargets and Therapy. Volume 10. 1921–1932. 53 indexed citations
9.
Townsend, Michelle H., et al.. (2017). Evaluation of various glyphosate concentrations on DNA damage in human Raji cells and its impact on cytotoxicity. Regulatory Toxicology and Pharmacology. 85. 79–85. 27 indexed citations
10.
Martínez, Gabriel, et al.. (2015). The Antioxidant and DNA Repair Activities of Resveratrol, Piceatannol, and Pterostilbene. Journal of Food Research. 4(5). 9–9. 3 indexed citations
11.
Robison, Richard A., et al.. (2014). DNA damage caused by inorganic particulate matter on Raji and HepG2 cell lines exposed to ultraviolet radiation. Mutation Research/Genetic Toxicology and Environmental Mutagenesis. 771. 6–14. 6 indexed citations
12.
O’Neill, Kim L., et al.. (2014). PCR-based Methodologies Used to Detect and Differentiate theBurkholderia pseudomalleicomplex:B. pseudomallei,B. mallei, andB. thailandensis. Current Issues in Molecular Biology. 24 indexed citations
13.
Stewart, Cameron, et al.. (2010). Cytotoxicity ofAtriplex confertifolia. Journal of Toxicology. 2010. 1–7. 17 indexed citations
14.
Tomer, David P., et al.. (2007). Comparison of the Total Oxyradical Scavenging Capacity and Oxygen Radical Absorbance Capacity Antioxidant Assays. Journal of Medicinal Food. 10(2). 337–344. 16 indexed citations
15.
Meier, Kevin, et al.. (2005). Tannic acid derivatives display anti-angiogenic properties in human breast cancer cells by interfering with CXCR4/SDF-1 interactions. Cancer Research. 65. 1225–1225. 2 indexed citations
16.
O’Neill, Kim L., et al.. (2005). Development of a novel human vestibular schwannoma xenograft model in SCID mice. Cancer Research. 65. 1394–1394. 1 indexed citations
17.
Husseini, Ghaleb A., Kim L. O’Neill, & William G. Pitt. (2005). The Comet Assay to Determine the Mode of Cell Death for the Ultrasonic Delivery of Doxorubicin to Human Leukemia (HL-60 Cells) from Pluronic P105 Micelles. Technology in Cancer Research & Treatment. 4(6). 707–711. 34 indexed citations
18.
London, Nyall R., et al.. (2004). Tannic acid prevents angiogenesis in vivo by inhibiting CXCR4/SDF-1 alpha binding in breast cancer cells. Cancer Research. 64. 12–12. 4 indexed citations
19.
Zhang, Fuquan, et al.. (2001). A Monoclonal Antibody Specific for Human Thymidine Kinase 1. Hybridoma. 20(1). 25–34. 16 indexed citations
20.
Fairbairn, Daryl W., et al.. (1993). Differential DNA Damage Detected in Hybridomas. Hybridoma. 12(6). 755–761. 7 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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