Tamar E. Boursalian

1.4k total citations
18 papers, 1.2k citations indexed

About

Tamar E. Boursalian is a scholar working on Immunology, Radiology, Nuclear Medicine and Imaging and Molecular Biology. According to data from OpenAlex, Tamar E. Boursalian has authored 18 papers receiving a total of 1.2k indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Immunology, 6 papers in Radiology, Nuclear Medicine and Imaging and 5 papers in Molecular Biology. Recurrent topics in Tamar E. Boursalian's work include T-cell and B-cell Immunology (12 papers), Immune Cell Function and Interaction (8 papers) and Monoclonal and Polyclonal Antibodies Research (6 papers). Tamar E. Boursalian is often cited by papers focused on T-cell and B-cell Immunology (12 papers), Immune Cell Function and Interaction (8 papers) and Monoclonal and Polyclonal Antibodies Research (6 papers). Tamar E. Boursalian collaborates with scholars based in United States, Denmark and Australia. Tamar E. Boursalian's co-authors include Pamela J. Fink, J. Scott Hale, Kim Bottomly, Jonathan L. Golob, David M. Soper, Cristine J. Cooper, Che‐Leung Law, Julie A. McEarchern, Iqbal S. Grewal and Stefan F. Martin and has published in prestigious journals such as Proceedings of the National Academy of Sciences, The Journal of Experimental Medicine and Nature Immunology.

In The Last Decade

Tamar E. Boursalian

18 papers receiving 1.2k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Tamar E. Boursalian United States 16 863 324 210 112 97 18 1.2k
Kathy Barrett United Kingdom 11 435 0.5× 355 1.1× 252 1.2× 205 1.8× 109 1.1× 20 1.1k
Lynn Ogata United States 7 913 1.1× 216 0.7× 146 0.7× 41 0.4× 170 1.8× 8 1.2k
David Coe United Kingdom 18 681 0.8× 247 0.8× 223 1.1× 55 0.5× 74 0.8× 27 1.1k
Lihe Su United States 15 577 0.7× 450 1.4× 150 0.7× 108 1.0× 95 1.0× 26 1.1k
Syuichi Nakatsuru Japan 10 523 0.6× 336 1.0× 222 1.1× 100 0.9× 114 1.2× 10 1.0k
Jacqueline M. Slavik United States 10 628 0.7× 264 0.8× 190 0.9× 51 0.5× 191 2.0× 13 997
Sandra J. Saouaf United States 12 986 1.1× 545 1.7× 227 1.1× 80 0.7× 116 1.2× 17 1.4k
Fanny Szafer Israel 11 377 0.4× 188 0.6× 101 0.5× 88 0.8× 126 1.3× 14 896
Peter C. Heinrich Germany 13 595 0.7× 352 1.1× 686 3.3× 109 1.0× 48 0.5× 13 1.2k
Walker R. Force United States 8 1.1k 1.3× 840 2.6× 268 1.3× 42 0.4× 94 1.0× 8 1.6k

Countries citing papers authored by Tamar E. Boursalian

Since Specialization
Citations

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

Fields of papers citing papers by Tamar E. Boursalian

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Tamar E. Boursalian. 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 Tamar E. Boursalian. The network helps show where Tamar E. Boursalian may publish in the future.

Co-authorship network of co-authors of Tamar E. Boursalian

This figure shows the co-authorship network connecting the top 25 collaborators of Tamar E. Boursalian. A scholar is included among the top collaborators of Tamar E. Boursalian 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 Tamar E. Boursalian. Tamar E. Boursalian 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.
Leung, Sherman S., Danielle J. Borg, Domenica A. McCarthy, et al.. (2022). Soluble RAGE Prevents Type 1 Diabetes Expanding Functional Regulatory T Cells. Diabetes. 71(9). 1994–2008. 16 indexed citations
2.
Rydén, Anna, Nikole Perdue, Philippe P. Pagni, et al.. (2017). Anti-IL-21 monoclonal antibody combined with liraglutide effectively reverses established hyperglycemia in mouse models of type 1 diabetes. Journal of Autoimmunity. 84. 65–74. 34 indexed citations
3.
Pham, Minh N., Anna Rydén, Nikole Perdue, et al.. (2016). Oral insulin (human, murine, or porcine) does not prevent diabetes in the non-obese diabetic mouse. Clinical Immunology. 164. 28–33. 17 indexed citations
4.
Okeley, Nicole M., Stephen C. Alley, Martha E. Anderson, et al.. (2013). Development of orally active inhibitors of protein and cellular fucosylation. Proceedings of the National Academy of Sciences. 110(14). 5404–5409. 147 indexed citations
5.
Houston, Evan, Tamar E. Boursalian, & Pamela J. Fink. (2012). Homeostatic signals do not drive post-thymic T cell maturation. Cellular Immunology. 274(1-2). 39–45. 19 indexed citations
6.
Law, Che‐Leung, May Kung Sutherland, Jamie B. Miyamoto, et al.. (2011). Abstract 625: Preclinical characterization of an auristatin-based anti-CD19 drug conjugate, SGN-19A. Cancer Research. 71(8_Supplement). 625–625. 5 indexed citations
7.
Hale, J. Scott, Kristina Ames, Tamar E. Boursalian, & Pamela J. Fink. (2010). Cutting Edge: Rag Deletion in Peripheral T Cells Blocks TCR Revision. The Journal of Immunology. 184(11). 5964–5968. 15 indexed citations
8.
Oflazoglu, Ezogelin, Tamar E. Boursalian, Weiping Zeng, et al.. (2009). Blocking of CD27-CD70 Pathway by Anti-CD70 Antibody Ameliorates Joint Disease in Murine Collagen-Induced Arthritis. The Journal of Immunology. 183(6). 3770–3777. 47 indexed citations
9.
Boursalian, Tamar E., Julie A. McEarchern, Che‐Leung Law, & Iqbal S. Grewal. (2009). Targeting CD70 for Human Therapeutic Use. Advances in experimental medicine and biology. 647. 108–119. 36 indexed citations
10.
McEarchern, Julie A., Leia M. Smith, Charlotte F. McDonagh, et al.. (2008). Preclinical Characterization of SGN-70, a Humanized Antibody Directed against CD70. Clinical Cancer Research. 14(23). 7763–7772. 70 indexed citations
11.
Hale, J. Scott, et al.. (2006). Thymic output in aged mice. Proceedings of the National Academy of Sciences. 103(22). 8447–8452. 248 indexed citations
12.
Dao, Tao, Alexander Ploß, Carolyn Saylor, et al.. (2004). Development of CD1d‐restricted NKT cells in the mouse thymus. European Journal of Immunology. 34(12). 3542–3552. 39 indexed citations
13.
Boursalian, Tamar E., Jonathan L. Golob, David M. Soper, Cristine J. Cooper, & Pamela J. Fink. (2004). Continued maturation of thymic emigrants in the periphery. Nature Immunology. 5(4). 418–425. 253 indexed citations
14.
Boursalian, Tamar E. & Pamela J. Fink. (2003). Mutation in Fas Ligand Impairs Maturation of Thymocytes Bearing Moderate Affinity T Cell Receptors. The Journal of Experimental Medicine. 198(2). 349–360. 22 indexed citations
15.
Suzuki, Ivy, Stefan F. Martin, Tamar E. Boursalian, Courtney Beers, & Pamela J. Fink. (2000). Fas Ligand Costimulates the In Vivo Proliferation of CD8+ T Cells. The Journal of Immunology. 165(10). 5537–5543. 95 indexed citations
16.
Boursalian, Tamar E. & Kim Bottomly. (1999). Survival of Naive CD4 T Cells: Roles of Restricting Versus Selecting MHC Class II and Cytokine Milieu. The Journal of Immunology. 162(7). 3795–3801. 88 indexed citations
17.
Boursalian, Tamar E. & Kim Bottomly. (1999). Stability of Naive and Memory Phenotypes on Resting CD4 T Cells In Vivo. The Journal of Immunology. 162(1). 9–16. 31 indexed citations
18.
Janeway, Charles A., Abraham Kupfer, Christophe Viret, et al.. (1998). T-cell development, survival, and signalling: A new concept of the role of self-peptide: Self-MHC complexes. 6(1). 5–12. 13 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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