Peter R. Rhode

3.2k total citations
57 papers, 2.0k citations indexed

About

Peter R. Rhode is a scholar working on Immunology, Oncology and Molecular Biology. According to data from OpenAlex, Peter R. Rhode has authored 57 papers receiving a total of 2.0k indexed citations (citations by other indexed papers that have themselves been cited), including 36 papers in Immunology, 28 papers in Oncology and 13 papers in Molecular Biology. Recurrent topics in Peter R. Rhode's work include Immune Cell Function and Interaction (28 papers), CAR-T cell therapy research (22 papers) and Immunotherapy and Immune Responses (13 papers). Peter R. Rhode is often cited by papers focused on Immune Cell Function and Interaction (28 papers), CAR-T cell therapy research (22 papers) and Immunotherapy and Immune Responses (13 papers). Peter R. Rhode collaborates with scholars based in United States, Netherlands and Germany. Peter R. Rhode's co-authors include Hing C. Wong, Judith L. Campbell, Emily K. Jeng, Xiaoyun Zhu, Kaiping Han, Warren D. Marcus, Kevin Sweder, Lin Kong, Jack O. Egan and Wenxin Xu and has published in prestigious journals such as Journal of Biological Chemistry, Journal of Clinical Oncology and Genes & Development.

In The Last Decade

Peter R. Rhode

54 papers receiving 2.0k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Peter R. Rhode United States 22 1.1k 853 491 365 257 57 2.0k
Stefano Sammicheli Sweden 14 1.4k 1.3× 901 1.1× 384 0.8× 211 0.6× 106 0.4× 23 2.0k
Elie Marcheteau France 12 1.0k 1.0× 1.5k 1.8× 594 1.2× 129 0.4× 205 0.8× 20 2.4k
Jason Stadanlick United States 21 1.0k 0.9× 246 0.3× 246 0.5× 269 0.7× 327 1.3× 32 1.6k
Ligia Craciun Belgium 20 1.1k 1.1× 865 1.0× 457 0.9× 133 0.4× 90 0.4× 49 2.0k
Won‐Tak Choi United States 23 280 0.3× 547 0.6× 217 0.4× 322 0.9× 188 0.7× 91 1.3k
Joop Gäken United Kingdom 28 486 0.4× 484 0.6× 1.2k 2.5× 192 0.5× 173 0.7× 68 2.5k
Anupam M. Desai United States 7 870 0.8× 1.3k 1.5× 357 0.7× 126 0.3× 69 0.3× 11 1.9k
Lise Boussemart France 11 261 0.2× 722 0.8× 830 1.7× 175 0.5× 211 0.8× 17 1.6k
Itziar Otano Spain 17 620 0.6× 681 0.8× 331 0.7× 241 0.7× 131 0.5× 28 1.3k
Satoko Matsueda Japan 24 1.2k 1.1× 935 1.1× 713 1.5× 130 0.4× 53 0.2× 85 1.8k

Countries citing papers authored by Peter R. Rhode

Since Specialization
Citations

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

Fields of papers citing papers by Peter R. Rhode

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Peter R. Rhode. 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 Peter R. Rhode. The network helps show where Peter R. Rhode may publish in the future.

Co-authorship network of co-authors of Peter R. Rhode

This figure shows the co-authorship network connecting the top 25 collaborators of Peter R. Rhode. A scholar is included among the top collaborators of Peter R. Rhode 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 Peter R. Rhode. Peter R. Rhode 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.
Zhu, Xiaoyun, Qiongzhen Li, Niraj Shrestha, et al.. (2023). A novel interleukin-2-based fusion molecule, HCW9302, differentially promotes regulatory T cell expansion to treat atherosclerosis in mice. Frontiers in Immunology. 14. 1114802–1114802. 6 indexed citations
2.
Geller, Melissa A., Manish R. Patel, Hing C. Wong, et al.. (2023). 767 Pre-clinical and first-in-human studies of HCW9218, a bifunctional TGF-β antagonist/IL-15 protein complex, in advanced solid tumors. SHILAP Revista de lepidopterología. A862–A862.
3.
Furuya, Hideki, Owen Chan, Ian Pagano, et al.. (2019). Effectiveness of two different dose administration regimens of an IL-15 superagonist complex (ALT-803) in an orthotopic bladder cancer mouse model. Journal of Translational Medicine. 17(1). 29–29. 20 indexed citations
4.
Margolin, Kim, Chihiro Morishima, Vamsidhar Velcheti, et al.. (2018). Phase I Trial of ALT-803, A Novel Recombinant IL15 Complex, in Patients with Advanced Solid Tumors. Clinical Cancer Research. 24(22). 5552–5561. 146 indexed citations
5.
6.
7.
Liu, Bai, Lin Kong, Kaiping Han, et al.. (2016). A Novel Fusion of ALT-803 (Interleukin (IL)-15 Superagonist) with an Antibody Demonstrates Antigen-specific Antitumor Responses. Journal of Biological Chemistry. 291(46). 23869–23881. 60 indexed citations
8.
Rhode, Peter R., Jack O. Egan, Wenxin Xu, et al.. (2015). Comparison of the Superagonist Complex, ALT-803, to IL15 as Cancer Immunotherapeutics in Animal Models. Cancer Immunology Research. 4(1). 49–60. 170 indexed citations
9.
Gomes-Giacoia, Evan, Makito Miyake, Steve Goodison, et al.. (2014). Intravesical ALT-803 and BCG Treatment Reduces Tumor Burden in a Carcinogen Induced Bladder Cancer Rat Model; a Role for Cytokine Production and NK Cell Expansion. PLoS ONE. 9(6). e96705–e96705. 78 indexed citations
10.
Xu, Wenxin, Monica Jones, Bai Liu, et al.. (2013). Efficacy and Mechanism-of-Action of a Novel Superagonist Interleukin-15: Interleukin-15 Receptor αSu/Fc Fusion Complex in Syngeneic Murine Models of Multiple Myeloma. Cancer Research. 73(10). 3075–3086. 157 indexed citations
11.
12.
Zhu, Xiaoyun, Warren D. Marcus, Wenxin Xu, et al.. (2009). Novel Human Interleukin-15 Agonists. The Journal of Immunology. 183(6). 3598–3607. 123 indexed citations
13.
Bömmel, Florian van, Robert A. de Man, Heiner Wedemeyer, et al.. (2009). Long-Term Efficacy of Tenofovir Monotherapy for Hepatitis B Virus-Monoinfected Patients After Failure of Nucleoside/Nucleotide Analogues. Hepatology. 51(1). 73–80. 264 indexed citations
14.
Wen, Jinghai, Xiaoyun Zhu, Bai Liu, et al.. (2008). Targeting activity of a TCR/IL-2 fusion protein against established tumors. Cancer Immunology Immunotherapy. 57(12). 1781–1794. 23 indexed citations
15.
You, Lijing, Kaiping Han, Hyung‐il Lee, et al.. (2007). Peptide-loading enhancement for antigen presenting cells (93.6). The Journal of Immunology. 178(1_Supplement). S167–S167. 1 indexed citations
16.
Zhu, Xiaoyun, Shari A. Price‐Schiavi, Hyung‐il Lee, et al.. (2006). Visualization of p53264–272/HLA-A*0201 Complexes Naturally Presented on Tumor Cell Surface by a Multimeric Soluble Single-Chain T Cell Receptor. The Journal of Immunology. 176(5). 3223–3232. 24 indexed citations
17.
Price‐Schiavi, Shari A., Bai Liu, Hyung‐il Lee, et al.. (2006). Potent antitumor activity of a tumor-specific soluble TCR/IL-2 fusion protein. Clinical Immunology. 121(1). 29–39. 18 indexed citations
18.
Rhode, Peter R., et al.. (1996). Single-chain MHC class II molecules induce T cell activation and apoptosis. The Journal of Immunology. 157(11). 4885–4891. 34 indexed citations
19.
Rhode, Peter R., Suzanne Elsasser, & Judith L. Campbell. (1992). Role of Multifunctional Autonomously Replicating Sequence Binding Factor 1 in the Initiation of DNA Replication and Transcriptional Control in Saccharomyces cerevisiae. Molecular and Cellular Biology. 12(3). 1064–1077. 33 indexed citations
20.
Rhode, Peter R. & Jack Gorski. (1991). Growth and cell cycle regulation of mRNA levels in GH3 cells. Molecular and Cellular Endocrinology. 82(1). 11–22. 20 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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