Mark Selby

14.3k total citations · 2 hit papers
96 papers, 9.6k citations indexed

About

Mark Selby is a scholar working on Immunology, Oncology and Molecular Biology. According to data from OpenAlex, Mark Selby has authored 96 papers receiving a total of 9.6k indexed citations (citations by other indexed papers that have themselves been cited), including 23 papers in Immunology, 21 papers in Oncology and 20 papers in Molecular Biology. Recurrent topics in Mark Selby's work include Cancer Immunotherapy and Biomarkers (16 papers), Advancements in Solid Oxide Fuel Cells (15 papers) and Hepatitis C virus research (15 papers). Mark Selby is often cited by papers focused on Cancer Immunotherapy and Biomarkers (16 papers), Advancements in Solid Oxide Fuel Cells (15 papers) and Hepatitis C virus research (15 papers). Mark Selby collaborates with scholars based in United States, United Kingdom and Japan. Mark Selby's co-authors include William J. Rutter, Alan J. Korman, Graeme I. Bell, Changyu Wang, Michael Houghton, Charles G. Drake, Robert H. Edwards, Robert A. Anders, Alice Pons and William H. Sharfman and has published in prestigious journals such as Nature, Science and Cell.

In The Last Decade

Mark Selby

92 papers receiving 9.2k citations

Hit Papers

Phase I Study of Single-Agent Anti–Programmed Death-1 (MD... 2010 2026 2015 2020 2010 2014 500 1000 1.5k 2.0k

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Mark Selby United States 42 3.4k 3.2k 3.0k 1.3k 1.3k 96 9.6k
Fernando Arenzana‐Seisdedos France 58 6.3k 1.8× 7.1k 2.2× 5.0k 1.7× 1.6k 1.2× 674 0.5× 93 16.9k
Thomas Bugge United States 62 1.9k 0.6× 1.6k 0.5× 4.5k 1.5× 828 0.6× 668 0.5× 165 11.2k
Masahiko Kuroda Japan 47 2.3k 0.7× 2.2k 0.7× 7.1k 2.4× 1.2k 0.9× 365 0.3× 228 12.2k
Hanswalter Zentgraf Germany 68 2.0k 0.6× 1.4k 0.4× 7.9k 2.6× 2.5k 1.9× 781 0.6× 226 14.1k
David Buck United Kingdom 37 2.5k 0.7× 3.0k 0.9× 3.7k 1.2× 558 0.4× 167 0.1× 66 9.1k
Shoshana Levy United States 60 1.3k 0.4× 4.3k 1.3× 3.9k 1.3× 1.7k 1.3× 2.2k 1.7× 137 11.3k
Arie Abo United States 41 4.3k 1.3× 2.6k 0.8× 8.7k 2.9× 394 0.3× 449 0.3× 56 15.1k
Stephen C. Peiper United States 59 4.2k 1.2× 6.6k 2.1× 4.3k 1.4× 1.2k 0.9× 216 0.2× 178 14.1k
Victor Koteliansky United States 57 1.8k 0.5× 3.0k 0.9× 10.3k 3.4× 1.7k 1.2× 897 0.7× 125 17.2k
Hamid Band United States 60 3.0k 0.9× 4.0k 1.2× 6.1k 2.0× 673 0.5× 242 0.2× 199 11.4k

Countries citing papers authored by Mark Selby

Since Specialization
Citations

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

Fields of papers citing papers by Mark Selby

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Mark Selby

This figure shows the co-authorship network connecting the top 25 collaborators of Mark Selby. A scholar is included among the top collaborators of Mark Selby 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 Mark Selby. Mark Selby 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.
Fesen, Robert A., Daniel Patnaude, Wei-Hao Wang, et al.. (2025). Deep Optical Images of the Ejecta Nebula around the Wolf–Rayet Star WR 8 (HD 62910). The Astronomical Journal. 169(4). 231–231. 1 indexed citations
2.
Selby, Mark, et al.. (2024). Abstract 5243: CAR B cells to accelerate antigen presentation in cancer. Cancer Research. 84(6_Supplement). 5243–5243.
3.
Thudium, Kent, Mark Selby, Julie A. Zorn, et al.. (2022). Preclinical Characterization of Relatlimab, a Human LAG-3–Blocking Antibody, Alone or in Combination with Nivolumab. Cancer Immunology Research. 10(10). 1175–1189. 55 indexed citations
4.
McDonald, Bryan, Nathan O. Siemers, Mark Selby, et al.. (2021). Fc-Optimized Anti-CCR8 Antibody Depletes Regulatory T Cells in Human Tumor Models. Cancer Research. 81(11). 2983–2994. 76 indexed citations
5.
Hjalmarsson, Per, et al.. (2021). 1MW-Class Solid Oxide Electrolyser System Prototype for Low-Cost Green Hydrogen. ECS Transactions. 103(1). 383–392. 11 indexed citations
6.
7.
Selby, Mark, et al.. (2019). <p>Aryl hydrocarbon receptor acts as a tumor suppressor in a syngeneic MC38 colon carcinoma tumor model</p>. PubMed. Volume 7. 1–16. 12 indexed citations
8.
Sidney, John, et al.. (2019). Identification of epitopes in ovalbumin that provide insights for cancer neoepitopes. JCI Insight. 4(8). 18 indexed citations
9.
Leah, Robert, Ahmet Selçuk, Mahfujur Rahman, et al.. (2017). Development Progress on the Ceres Power Steel Cell Technology Platform: Further Progress Towards Commercialization. ECS Meeting Abstracts. MA2017-03(1). 7–7. 2 indexed citations
10.
Wang, Changyu, Kent Thudium, Minhua Han, et al.. (2014). In Vitro Characterization of the Anti-PD-1 Antibody Nivolumab, BMS-936558, and In Vivo Toxicology in Non-Human Primates. Cancer Immunology Research. 2(9). 846–856. 472 indexed citations breakdown →
11.
Korman, Alan J., Bing Chen, Changyu Wang, et al.. (2007). Activity of Anti-PD-1 in Murine Tumor Models: Role of “Host” PD-L1 and Synergistic Effect of Anti-PD-1 and Anti-CTLA-4 (48.37). The Journal of Immunology. 178(1_Supplement). S82–S82. 40 indexed citations
12.
Polakos, Noelle K., Debbie Drane, John C. Cox, et al.. (2001). Characterization of Hepatitis C Virus Core-Specific Immune Responses Primed in Rhesus Macaques by a Nonclassical ISCOM Vaccine. The Journal of Immunology. 166(5). 3589–3598. 75 indexed citations
13.
Widera, Georg, Melissa A. Austin, Dietmar Rabussay, et al.. (2000). Increased DNA Vaccine Delivery and Immunogenicity by Electroporation In Vivo. The Journal of Immunology. 164(9). 4635–4640. 445 indexed citations
14.
Dupuis, Marc, Kimberly Denis-Mize, Cheryl Goldbeck, et al.. (2000). Distribution of DNA Vaccines Determines Their Immunogenicity After Intramuscular Injection in Mice. The Journal of Immunology. 165(5). 2850–2858. 261 indexed citations
15.
Ni, Yongnian, Mark Selby, Serge Kokot, & M. C. Hodgkinson. (1993). Curve resolution and quantification of pyrazines by differential-pulse polarography using a Kalman filter approach. The Analyst. 118(8). 1049–1049. 15 indexed citations
17.
Selby, Mark, et al.. (1989). End use markets for MSW compost.. Biocycle. 30(11). 56–58. 3 indexed citations
18.
Edwards, Robert H., Mark Selby, William C. Mobley, et al.. (1988). Processing and Secretion of Nerve Growth Factor: Expression in Mammalian Cells with a Vaccinia Virus Vector. Molecular and Cellular Biology. 8(6). 2456–2464. 29 indexed citations
19.
Moore, T. J. T., C. M. Mountain, T. Yamashita, & Mark Selby. (1988). New near-infrared sources and reflection nebulosity in W75N. Monthly Notices of the Royal Astronomical Society. 234(1). 95–105. 9 indexed citations
20.
Scott, James, Mickey S. Urdea, Margarita Quiroga, et al.. (1983). Structure of a Mouse Submaxillary Messenger RNA Encoding Epidermal Growth Factor and Seven Related Proteins. Science. 221(4607). 236–240. 392 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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