Wayne Kindsvogel

4.3k total citations · 1 hit paper
20 papers, 2.0k citations indexed

About

Wayne Kindsvogel is a scholar working on Molecular Biology, Immunology and Pathology and Forensic Medicine. According to data from OpenAlex, Wayne Kindsvogel has authored 20 papers receiving a total of 2.0k indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Molecular Biology, 8 papers in Immunology and 7 papers in Pathology and Forensic Medicine. Recurrent topics in Wayne Kindsvogel's work include Lymphoma Diagnosis and Treatment (7 papers), Immune Cell Function and Interaction (6 papers) and Pancreatic function and diabetes (5 papers). Wayne Kindsvogel is often cited by papers focused on Lymphoma Diagnosis and Treatment (7 papers), Immune Cell Function and Interaction (6 papers) and Pancreatic function and diabetes (5 papers). Wayne Kindsvogel collaborates with scholars based in United States, France and Denmark. Wayne Kindsvogel's co-authors include Jane A. Gross, Christopher H. Clegg, Hal Blumberg, Stacey R. Dillon, Harald S. Haugen, Kevin P. Foley, Margaret Moore, Don Foster, Wenfeng Xu and Janet Johnston and has published in prestigious journals such as Nature, Nucleic Acids Research and Journal of Biological Chemistry.

In The Last Decade

Wayne Kindsvogel

20 papers receiving 2.0k citations

Hit Papers

TACI and BCMA are receptors for a TNF homologue implicate... 2000 2026 2008 2017 2000 250 500 750

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Wayne Kindsvogel United States 10 1.1k 559 395 340 332 20 2.0k
H Kitayama Japan 19 998 0.9× 903 1.6× 355 0.9× 122 0.4× 248 0.7× 49 2.2k
Ching Chen United States 20 1.0k 0.9× 619 1.1× 191 0.5× 420 1.2× 213 0.6× 31 1.9k
Grazyna Adamus United States 34 504 0.5× 1.1k 2.0× 228 0.6× 224 0.7× 530 1.6× 92 3.0k
I G Rennie United Kingdom 29 331 0.3× 831 1.5× 680 1.7× 487 1.4× 92 0.3× 136 2.8k
Gerd Munzert Germany 28 436 0.4× 1.4k 2.6× 1.1k 2.7× 398 1.2× 52 0.2× 63 3.1k
Delphine Loussouarn France 28 333 0.3× 976 1.7× 694 1.8× 122 0.4× 68 0.2× 76 2.3k
Lorraine Lipfert United States 18 201 0.2× 1.2k 2.1× 410 1.0× 229 0.7× 60 0.2× 20 2.4k
Harald Illges Germany 21 772 0.7× 479 0.9× 151 0.4× 224 0.7× 228 0.7× 57 1.4k
Anne Mette Buhl Denmark 21 958 0.9× 1.0k 1.8× 329 0.8× 222 0.7× 42 0.1× 31 2.1k
Khuda Dad Khan United States 16 512 0.5× 622 1.1× 715 1.8× 142 0.4× 22 0.1× 29 1.5k

Countries citing papers authored by Wayne Kindsvogel

Since Specialization
Citations

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

Fields of papers citing papers by Wayne Kindsvogel

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Wayne Kindsvogel

This figure shows the co-authorship network connecting the top 25 collaborators of Wayne Kindsvogel. A scholar is included among the top collaborators of Wayne Kindsvogel 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 Wayne Kindsvogel. Wayne Kindsvogel 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
3.
Roda, Julie M., Aruna Gowda, Rehan M. Hussain, et al.. (2007). IL-21 Promotes Apoptosis through Induction of the BH3 Only Protein Bim and Enhacnes Direct and Innate Immune-Promoted Death of Chronic Lymphocytic Leukemia Cells.. Blood. 110(11). 3118–3118. 1 indexed citations
4.
Gowda, Aruna, Asha Ramanunni, Carolyn Cheney, et al.. (2007). IL-21 enhances chemoimmunotherapy mediated death of chronic lymphocytic leukemia cells. Journal of Clinical Oncology. 25(18_suppl). 7094–7094. 1 indexed citations
5.
Sarosiek, Kristopher A., Jun Chen, Hovav Nechushtan, et al.. (2006). Interleukin-21-Induced Apoptosis and Cell Death of Diffuse Large B-Cell Lymphoma (DLBCL) Cell Lines and Primary Tumors Are Associated with an Induction of Bim.. Blood. 108(11). 2503–2503. 2 indexed citations
6.
Hughes, S., Cecile M. Krejsa, Frank Wagner, et al.. (2005). IL-21 enhancement of rituximab-mediated B cell depletion. Journal of Clinical Oncology. 23(16_suppl). 2568–2568. 2 indexed citations
7.
Kindsvogel, Wayne, S. Hughes, Mark Heipel, et al.. (2004). IL-21 enhances rituximab-mediated killing of B-lymphoma cell lines in vitro and in vivo. Journal of Clinical Oncology. 22(14_suppl). 2581–2581. 3 indexed citations
8.
Krejsa, Cecile M., Mark Heipel, Rick D. Holly, et al.. (2004). Mechanisms of IL-21 Enhancement of Rituximab Efficacy in a Lymphoma Xenograft Model.. Blood. 104(11). 1404–1404. 1 indexed citations
9.
Kindsvogel, Wayne, S. Hughes, Mark Heipel, et al.. (2004). IL-21 enhances rituximab-mediated killing of B-lymphoma cell lines in vitro and in vivo. Journal of Clinical Oncology. 22(14_suppl). 2581–2581. 5 indexed citations
10.
Novak, Anne J., Jaime Darce, Bonnie K. Arendt, et al.. (2003). Expression of BCMA, TACI, and BAFF-R in multiple myeloma: a mechanism for growth and survival. Blood. 103(2). 689–694. 422 indexed citations
11.
Gross, Jane A., Janet Johnston, Sherri Mudri, et al.. (2000). TACI and BCMA are receptors for a TNF homologue implicated in B-cell autoimmune disease. Nature. 404(6781). 995–999. 967 indexed citations breakdown →
12.
Hansen, Lars, et al.. (1998). Glucagon-mediated Ca2+signaling in BHK cells expressing cloned human glucagon receptors. American Journal of Physiology-Cell Physiology. 274(6). C1552–C1562. 47 indexed citations
14.
Hansen, Lars, Niels Abrahamsen, Jörg Hager, et al.. (1996). The Gly40Ser Mutation in the Human Glucagon Receptor Gene Associated With NIDDM Results in a Receptor With Reduced Sensitivity to Glucagon. Diabetes. 45(6). 725–730. 33 indexed citations
15.
Hansen, Lone, Christian Vaisse, Nathalie Vionnet, et al.. (1995). A missense mutation in the glucagon receptor gene is associated with non–insulin–dependent diabetes mellitus. Nature Genetics. 9(3). 299–304. 126 indexed citations
16.
Lok, Si, Joseph L. Kuijper, Janet Kramer, et al.. (1994). The human glucagon receptor encoding gene: structure, cDNA sequence and chromosomal localization. Gene. 140(2). 203–209. 95 indexed citations
17.
Wayman, Gary A., Soren Impey, Zhiliang Wu, et al.. (1994). Synergistic activation of the type I adenylyl cyclase by Ca2+ and Gs-coupled receptors in vivo.. Journal of Biological Chemistry. 269(41). 25400–25405. 115 indexed citations
18.
Hu, Jinyue, Wayne Kindsvogel, Stephen Busby, et al.. (1993). An evaluation of the potential to use tumor-associated antigens as targets for antitumor T cell therapy using transgenic mice expressing a retroviral tumor antigen in normal lymphoid tissues.. The Journal of Experimental Medicine. 177(6). 1681–1690. 53 indexed citations
19.
Grant, Francis James, Steven D. Levin, Terri L. Gilbert, & Wayne Kindsvogel. (1987). Improved RNA sequencing method to determine immunoglobulin mRNA sequence. Nucleic Acids Research. 15(13). 5496–5496. 2 indexed citations
20.
Kindsvogel, Wayne, et al.. (1982). A Cloned cDNA Probe for Rat Immunoglobulin Epsilon Heavy Chain: Construction, Identification, and DNA Sequence. DNA. 1(4). 335–343. 3 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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