John M. Timmerman

2.4k total citations
28 papers, 1.8k citations indexed

About

John M. Timmerman is a scholar working on Immunology, Radiology, Nuclear Medicine and Imaging and Oncology. According to data from OpenAlex, John M. Timmerman has authored 28 papers receiving a total of 1.8k indexed citations (citations by other indexed papers that have themselves been cited), including 24 papers in Immunology, 21 papers in Radiology, Nuclear Medicine and Imaging and 13 papers in Oncology. Recurrent topics in John M. Timmerman's work include Immunotherapy and Immune Responses (22 papers), Monoclonal and Polyclonal Antibodies Research (21 papers) and CAR-T cell therapy research (11 papers). John M. Timmerman is often cited by papers focused on Immunotherapy and Immune Responses (22 papers), Monoclonal and Polyclonal Antibodies Research (21 papers) and CAR-T cell therapy research (11 papers). John M. Timmerman collaborates with scholars based in United States, Netherlands and Belgium. John M. Timmerman's co-authors include Ronald Levy, Debra K. Czerwinski, Frank J. Hsu, Clemens B. Caspar, Behnaz Taidi, Ranjani Rajapaksa, Sara A. Hurvitz, David J. Betting, Wen‐Kai Weng and Edgar G. Engleman and has published in prestigious journals such as Journal of Clinical Oncology, Blood and Immunity.

In The Last Decade

John M. Timmerman

27 papers receiving 1.8k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
John M. Timmerman United States 20 1.5k 806 635 492 218 28 1.8k
Behnaz Taidi United States 8 2.0k 1.4× 998 1.2× 786 1.2× 236 0.5× 232 1.1× 12 2.3k
Ralph Mocikat Germany 21 1.5k 1.0× 825 1.0× 788 1.2× 463 0.9× 64 0.3× 65 2.3k
Silvia von Mensdorff‐Pouilly Netherlands 28 900 0.6× 525 0.7× 1.2k 2.0× 841 1.7× 117 0.5× 58 2.0k
Solam Tsang United States 10 1.6k 1.1× 628 0.8× 1.3k 2.1× 360 0.7× 70 0.3× 11 2.2k
Rony Dahan Israel 19 1.4k 1.0× 771 1.0× 618 1.0× 587 1.2× 60 0.3× 26 2.1k
Idit Sagiv-Barfi United States 14 1.3k 0.9× 1.1k 1.4× 371 0.6× 156 0.3× 220 1.0× 32 1.9k
Jeffrey Schlom United States 17 821 0.6× 665 0.8× 793 1.2× 1000 2.0× 127 0.6× 37 1.9k
H. Bernhard Germany 19 876 0.6× 669 0.8× 459 0.7× 255 0.5× 96 0.4× 35 1.5k
Marit M. van Buuren Netherlands 12 1.7k 1.1× 1.7k 2.1× 680 1.1× 217 0.4× 90 0.4× 17 2.2k
Jasreet Hundal United States 13 2.1k 1.4× 2.0k 2.4× 1.3k 2.1× 356 0.7× 107 0.5× 21 3.1k

Countries citing papers authored by John M. Timmerman

Since Specialization
Citations

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

Fields of papers citing papers by John M. Timmerman

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by John M. Timmerman. 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 John M. Timmerman. The network helps show where John M. Timmerman may publish in the future.

Co-authorship network of co-authors of John M. Timmerman

This figure shows the co-authorship network connecting the top 25 collaborators of John M. Timmerman. A scholar is included among the top collaborators of John M. Timmerman 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 John M. Timmerman. John M. Timmerman 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.
Zettlitz, Kirstin A., et al.. (2017). ImmunoPET of Malignant and Normal B Cells with 89Zr- and 124I-Labeled Obinutuzumab Antibody Fragments Reveals Differential CD20 Internalization In Vivo. Clinical Cancer Research. 23(23). 7242–7252. 38 indexed citations
2.
Yamada, Douglas H., Heidi Elsaesser, Anja Lux, et al.. (2015). Suppression of Fcγ-Receptor-Mediated Antibody Effector Function during Persistent Viral Infection. Immunity. 42(2). 379–390. 51 indexed citations
3.
Betting, David J., Reiko Yamada, Kamran Kafi, et al.. (2009). Intratumoral But Not Systemic Delivery of CpG Oligodeoxynucleotide Augments the Efficacy of Anti-CD20 Monoclonal Antibody Therapy Against B Cell Lymphoma. Journal of Immunotherapy. 32(6). 622–631. 36 indexed citations
4.
Olafsen, Tove, David J. Betting, Vania Kenanova, et al.. (2009). Recombinant Anti-CD20 Antibody Fragments for Small-Animal PET Imaging of B-Cell Lymphomas. Journal of Nuclear Medicine. 50(9). 1500–1508. 63 indexed citations
5.
Betting, David J., et al.. (2008). Sulfhydryl-Based Tumor Antigen-Carrier Protein Conjugates Stimulate Superior Antitumor Immunity against B Cell Lymphomas. The Journal of Immunology. 181(6). 4131–4140. 32 indexed citations
6.
Kafi, Kamran, David J. Betting, Reiko Yamada, Karen F. Steward, & John M. Timmerman. (2008). Effect on in vivo immunogenicity of human idiotype-KLH vaccines by maleimide conjugation. Journal of Clinical Oncology. 26(15_suppl). 8576–8576. 1 indexed citations
7.
Timmerman, John M., et al.. (2008). Vaccine Therapies for Non-Hodgkin’s Lymphomas. Cancer treatment and research. 131. 283–315.
9.
Kafi, Kamran, et al.. (2008). Maleimide conjugation markedly enhances the immunogenicity of both human and murine idiotype-KLH vaccines. Molecular Immunology. 46(3). 448–456. 25 indexed citations
10.
Hurvitz, Sara A., David J. Betting, Josée Golay, et al.. (2006). Combination immunotherapy with rituximab and local delivery of CpG oligonucleotide in a syngeneic murine model expressing human CD20. Journal of Clinical Oncology. 24(18_suppl). 2502–2502. 1 indexed citations
11.
Hurvitz, Sara A. & John M. Timmerman. (2005). Recombinant, tumour-derived idiotype vaccination for indolent B cell non-Hodgkin’s lymphomas: a focus on FavId™. Expert Opinion on Biological Therapy. 5(6). 841–852. 26 indexed citations
12.
Hurvitz, Sara A. & John M. Timmerman. (2005). Current status of therapeutic vaccines for non-Hodgkin??s lymphoma. Current Opinion in Oncology. 17(5). 432–440. 26 indexed citations
13.
Timmerman, John M.. (2004). Therapeutic Idiotype Vaccines for Non-Hodgkin's Lymphoma. Advances in pharmacology. 51. 271–293. 6 indexed citations
14.
Timmerman, John M.. (2003). Immunotherapy for Lymphomas. International Journal of Hematology. 77(5). 444–455. 23 indexed citations
15.
Ribas, Antoni, John M. Timmerman, Lisa H. Butterfield, & James S. Economou. (2003). Determinant spreading and tumor responses after peptide-based cancer immunotherapy. Trends in Immunology. 24(2). 58–61. 93 indexed citations
16.
Timmerman, John M.. (2002). Vaccine therapies for Non-Hodgkin’s Lymphoma. Current Treatment Options in Oncology. 3(4). 307–315. 13 indexed citations
17.
Timmerman, John M., Clemens B. Caspar, Stacie Lambert, Athanasia Syrengelas, & Ronald Levy. (2001). Idiotype-encoding recombinant adenoviruses provide protective immunity against murine B-cell lymphomas. Blood. 97(5). 1370–1377. 57 indexed citations
18.
Timmerman, John M. & Ronald Levy. (2000). Linkage of Foreign Carrier Protein to a Self-Tumor Antigen Enhances the Immunogenicity of a Pulsed Dendritic Cell Vaccine. The Journal of Immunology. 164(9). 4797–4803. 101 indexed citations
19.
Timmerman, John M. & Ronald Levy. (2000). The History of the Development of Vaccines for the Treatment of Lymphoma. Clinical Lymphoma. 1(2). 129–139. 19 indexed citations
20.
Timmerman, John M. & Ronald Levy. (1999). Dendritic Cell Vaccines for Cancer Immunotherapy. Annual Review of Medicine. 50(1). 507–529. 409 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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