Larry W. Kwak

19.1k total citations · 2 hit papers
319 papers, 12.6k citations indexed

About

Larry W. Kwak is a scholar working on Immunology, Pathology and Forensic Medicine and Oncology. According to data from OpenAlex, Larry W. Kwak has authored 319 papers receiving a total of 12.6k indexed citations (citations by other indexed papers that have themselves been cited), including 155 papers in Immunology, 147 papers in Pathology and Forensic Medicine and 136 papers in Oncology. Recurrent topics in Larry W. Kwak's work include Lymphoma Diagnosis and Treatment (143 papers), Immunotherapy and Immune Responses (113 papers) and CAR-T cell therapy research (71 papers). Larry W. Kwak is often cited by papers focused on Lymphoma Diagnosis and Treatment (143 papers), Immunotherapy and Immune Responses (113 papers) and CAR-T cell therapy research (71 papers). Larry W. Kwak collaborates with scholars based in United States, China and Japan. Larry W. Kwak's co-authors include Arya Biragyn, Joost J. Oppenheim, Sattva S. Neelapu, De Yang, Qing Yi, Ronald Levy, Michael Wang, Luis Fayad, Debra K. Czerwinski and Pier Adelchi Ruffini and has published in prestigious journals such as Science, New England Journal of Medicine and Proceedings of the National Academy of Sciences.

In The Last Decade

Larry W. Kwak

309 papers receiving 12.4k citations

Hit Papers

Toll-Like Receptor 4-Depe... 2002 2026 2010 2018 2002 2002 200 400 600

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Larry W. Kwak United States 61 6.2k 4.9k 3.9k 3.2k 1.6k 319 12.6k
Alan Lichtenstein United States 52 1.9k 0.3× 3.3k 0.7× 4.8k 1.2× 1.0k 0.3× 1.3k 0.8× 162 10.5k
George J. Weiner United States 49 4.9k 0.8× 2.7k 0.5× 2.4k 0.6× 1.2k 0.4× 933 0.6× 180 8.8k
Christian Peschel Germany 69 4.9k 0.8× 5.2k 1.1× 5.8k 1.5× 1.8k 0.6× 2.7k 1.7× 345 16.8k
Jan G. J. van de Winkel Netherlands 70 8.9k 1.4× 2.7k 0.5× 5.6k 1.4× 1.1k 0.4× 1.4k 0.9× 246 17.2k
Hiroshi Shiku Japan 64 6.6k 1.1× 4.4k 0.9× 6.7k 1.7× 1.5k 0.5× 926 0.6× 535 16.3k
Eckhard Thiel Germany 57 3.4k 0.5× 3.1k 0.6× 3.1k 0.8× 2.7k 0.8× 2.7k 1.7× 260 11.9k
Christer Sundström Sweden 54 3.8k 0.6× 3.8k 0.8× 3.0k 0.8× 5.0k 1.6× 3.1k 1.9× 270 12.3k
Eva Klein Sweden 53 7.6k 1.2× 4.6k 0.9× 3.1k 0.8× 1.6k 0.5× 748 0.5× 310 13.0k
Jeffrey A. Ledbetter United States 52 10.4k 1.7× 2.6k 0.5× 3.8k 1.0× 801 0.2× 659 0.4× 118 14.8k
Gianpietro Semenzato Italy 60 6.0k 1.0× 2.6k 0.5× 2.8k 0.7× 2.9k 0.9× 3.2k 2.0× 475 14.6k

Countries citing papers authored by Larry W. Kwak

Since Specialization
Citations

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

Fields of papers citing papers by Larry W. Kwak

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Larry W. Kwak. 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 Larry W. Kwak. The network helps show where Larry W. Kwak may publish in the future.

Co-authorship network of co-authors of Larry W. Kwak

This figure shows the co-authorship network connecting the top 25 collaborators of Larry W. Kwak. A scholar is included among the top collaborators of Larry W. Kwak 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 Larry W. Kwak. Larry W. Kwak 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
2.
Wang, Lin, Tiantian Zhang, Joo Y. Song, et al.. (2024). Personalized neoantigen vaccines as early intervention in untreated patients with lymphoplasmacytic lymphoma: a non-randomized phase 1 trial. Nature Communications. 15(1). 6874–6874. 9 indexed citations
3.
Wang, Zhe, Tiantian Zhang, Vincent Lee, et al.. (2023). Immortalized B Cells Transfected with mRNA of Antigen Fused to MITD (IBMAM): An Effective Tool for Antigen-Specific T-Cell Expansion and TCR Validation. Biomedicines. 11(3). 796–796. 8 indexed citations
4.
Saumoy, Monica, Yecheskel Schneider, Lihua E. Budde, et al.. (2022). Cost-effectiveness of polatuzumab vedotin combined with chemoimmunotherapy in untreated diffuse large B-cell lymphoma. Blood. 140(25). 2697–2708. 14 indexed citations
5.
Buske, Christian, Wojciech Jurczak, Juan‐Manuel Sancho, et al.. (2021). Long-term efficacy and safety of CT-P10 or rituximab in untreated advanced follicular lymphoma: a randomized phase 3 study. Blood Advances. 5(17). 3354–3361. 6 indexed citations
6.
Dong, Zhenyuan, Wesley A. Cheng, D. Lynne Smith, et al.. (2020). Antitumor efficacy of BAFF-R targeting CAR T cells manufactured under clinic-ready conditions. Cancer Immunology Immunotherapy. 69(10). 2139–2145. 17 indexed citations
7.
Chen, Robert, Alex F. Herrera, Lu Chen, et al.. (2019). Inhibition of MDR1 Overcomes Resistance to Brentuximab Vedotin in Hodgkin Lymphoma. Clinical Cancer Research. 26(5). 1034–1044. 61 indexed citations
9.
Herrmann, Andreas, Christoph Lahtz, Toshikage Nagao, et al.. (2017). CTLA4 Promotes Tyk2-STAT3–Dependent B-cell Oncogenicity. Cancer Research. 77(18). 5118–5128. 38 indexed citations
10.
Qin, Hong, Guo‐Wei Wei, Ippei Sakamaki, et al.. (2017). Novel BAFF-Receptor Antibody to Natively Folded Recombinant Protein Eliminates Drug-Resistant Human B-cell Malignancies In Vivo. Clinical Cancer Research. 24(5). 1114–1123. 24 indexed citations
11.
Oki, Yasuhiro, Michelle A. Fanale, Jorge Romaguera, et al.. (2015). Phase II study of an AKT inhibitor MK2206 in patients with relapsed or refractory lymphoma. British Journal of Haematology. 171(4). 463–470. 68 indexed citations
12.
Qin, Hong, et al.. (2015). Targeting tumor-associated myeloid cells for cancer immunotherapy. OncoImmunology. 4(3). e983961–e983961. 8 indexed citations
13.
Strati, Paolo, Yasuhiro Oki, Luis Fayad, et al.. (2014). A Phase 1 Trial of Alisertib and Romidepsin for Relapsed/Refractory Aggressive B-Cell and T-Cell Lymphomas. Blood. 130(21). 4074–4074. 19 indexed citations
14.
Zhang, Liang, Lan V. Pham, Kate J. Newberry, et al.. (2013). In Vitro and In Vivo Therapeutic Efficacy of Carfilzomib in Mantle Cell Lymphoma: Targeting the Immunoproteasome. Molecular Cancer Therapeutics. 12(11). 2494–2504. 22 indexed citations
15.
He, Jin, Zhiqiang Liu, Yuhuan Zheng, et al.. (2012). p38 MAPK in Myeloma Cells Regulates Osteoclast and Osteoblast Activity and Induces Bone Destruction. Cancer Research. 72(24). 6393–6402. 69 indexed citations
16.
Zhang, Liang, Jing Yang, Jianfei Qian, et al.. (2012). Role of the microenvironment in mantle cell lymphoma: IL-6 is an important survival factor for the tumor cells. Blood. 120(18). 3783–3792. 88 indexed citations
17.
Ma, Wencai, Michael Wang, Zhiqiang Wang, et al.. (2010). Effect of Long-term Storage in TRIzol on Microarray-Based Gene Expression Profiling. Cancer Epidemiology Biomarkers & Prevention. 19(10). 2445–2452. 35 indexed citations
18.
19.
Neelapu, Sattva S., Larry W. Kwak, Carol B. Kobrin, et al.. (2005). Vaccine-induced tumor-specific immunity despite severe B-cell depletion in mantle cell lymphoma. Nature Medicine. 11(9). 986–991. 85 indexed citations
20.
Baskar, Sivasubramanian, Carol B. Kobrin, & Larry W. Kwak. (2004). Autologous lymphoma vaccines induce human T cell responses against multiple, unique epitopes. Journal of Clinical Investigation. 113(10). 1498–1510. 8 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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