Lawrence G. Lum
- Immunology top 1%
- Immunotherapy and Immune Responses 50
- Immune Cell Function and Interaction 33
- T-cell and B-cell Immunology 27
- Hematology top 1%
- Hematopoietic Stem Cell Transplantation 52
- Multiple Myeloma Research and Treatments 11
- Oncology top 1%
- CAR-T cell therapy research 80
- Cancer Immunotherapy and Biomarkers 22
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- Monoclonal and Polyclonal Antibodies Research 61
- Genetics top 5%
- Co-authors
- Archana ThakurAbhinav DeolWerner J. PichlerSamuel BroderRainer StorbPamela A. DavolR. Michael BlaeseJoseph P. Uberti
- Cited by
- ImmunologyHematologyOncology
- Journals
- New England Journal of Medicine (2 papers)Journal of Clinical Oncology (12 papers)SHILAP Revista de lepidopterología (1 paper)
- Partner nations
- United StatesCanadaSouth Africa
In The Last Decade
Lawrence G. Lum
207 papers receiving 4.5k citations
Peers
Comparison fields: 5 of 123
- Immunology 2.2k
- Hematology 971
- Oncology 1.9k
- Radiology, Nuclear Medicine and Imaging 1.1k
- Genetics 334
Countries citing papers authored by Lawrence G. Lum
This map shows the geographic impact of Lawrence G. Lum'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 Lawrence G. Lum with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Lawrence G. Lum more than expected).
Fields of papers citing papers by Lawrence G. Lum
This network shows the impact of papers produced by Lawrence G. Lum. 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 Lawrence G. Lum. The network helps show where Lawrence G. Lum may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Lawrence G. Lum, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2024 | 3 | |
| 2 | 2024 | 3 | |
| 3 | 2022 | 21 | |
| 4 | 2021 | 13 | |
| 5 | 2020 | 14 | |
| 6 | 2019 | 60 | |
| 7 | 2015 | 87 | |
| 8 | 2015 | 11 | |
| 9 | 2012 | 61 | |
| 10 | 2012 | 17 | |
| 11 | 2011 | 36 | |
| 12 | 2007 | 3 | |
| 13 | 2006 | 63 | |
| 14 | Preclinical studies comparing different bispecific antibodies for redirecting T cell cytotoxicity to extracellular antigens on prostate carcinomas. | 2005 | 14 |
| 15 | 2005 | 1 | |
| 16 | 2004 | 2 | |
| 17 | 2003 | 16 | |
| 18 | 2001 | 80 | |
| 19 | 1990 | 6 | |
| 20 | 1983 | 40 |
About Lawrence G. Lum
Lawrence G. Lum is a scholar working on Hematology, Immunology and Oncology, having authored 212 papers that have together received 4.7k indexed citations. Recurring topics across this work include CAR-T cell therapy research (80 papers), Monoclonal and Polyclonal Antibodies Research (61 papers), Hematopoietic Stem Cell Transplantation (52 papers), Immunotherapy and Immune Responses (50 papers), Immune Cell Function and Interaction (33 papers), T-cell and B-cell Immunology (27 papers), Cancer Immunotherapy and Biomarkers (22 papers) and Multiple Myeloma Research and Treatments (11 papers). The work is most often cited by research in Immunology (2.2k citations), Hematology (971 citations) and Oncology (1.9k citations). Lawrence G. Lum has collaborated with scholars based in United States, Canada and South Africa. Frequent co-authors include Archana Thakur, Abhinav Deol, Werner J. Pichler, Samuel Broder, Rainer Storb, Pamela A. Davol, R. Michael Blaese, Joseph P. Uberti, Manley Huang and Dana L. Schalk. Their work appears in journals such as New England Journal of Medicine, Journal of Clinical Oncology and SHILAP Revista de lepidopterología.
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.