David Wu
Impact in
- Hematology top 2%
- Acute Myeloid Leukemia Research
- Oncology top 2%
- CAR-T cell therapy research
Papers in
-
- Lymphoma Diagnosis and Treatment 21
- Hematology 19
- Acute Myeloid Leukemia Research 15
- Chronic Myeloid Leukemia Treatments 8
- Co-authors
- Brent L. Wood (22 shared papers)Jonathan R. Fromm (22 shared papers)Harlan Robins (8 shared papers)Min Fang (4 shared papers)David G. Maloney (3 shared papers)Sindhu Cherian (3 shared papers)Anna Sherwood (6 shared papers)Olivia Finney (1 shared paper)
- Journals
- Blood (10 papers)Cytometry Part B Clinical Cytometry (7 papers)American Journal of Clinical Pathology (7 papers)Journal of Molecular Diagnostics (3 papers)Biology of Blood and Marrow Transplantation (3 papers)
- Partner nations
- United StatesSouth AfricaGermany
In The Last Decade
David Wu
66 papers receiving 2.5k citations
David Wu's Hit Papers
Peers
Comparison fields: 5 of 81
- Hematology 515
- Oncology 1.1k
- Pathology and Forensic Medicine 496
- Immunology 560
- Genetics 260
Countries citing papers authored by David Wu
This map shows the geographic impact of David Wu'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 David Wu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites David Wu more than expected).
Fields of papers citing papers by David Wu
This network shows the impact of papers produced by David Wu. 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 David Wu. The network helps show where David Wu may publish in the future.
Co-authors
The 25 scholars most cited alongside David Wu, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 67 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Acquisition of a CD19-negative myeloid phenotype allows immune escape of MLL-rearranged B-ALL from CD19 CAR-T-cell therapy Hit paper breakdown → | 2016 | 575 |
| 2 | 2013 | 366 | |
| 3 | 2013 | 205 | |
| 4 | 2012 | 180 | |
| 5 | 2017 | 138 | |
| 6 | 2018 | 120 | |
| 7 | 2014 | 109 | |
| 8 | 2017 | 96 | |
| 9 | 2010 | 52 | |
| 10 | 2019 | 41 | |
| 11 | 2014 | 40 | |
| 12 | 2015 | 32 | |
| 13 | 2016 | 32 | |
| 14 | 2015 | 30 | |
| 15 | 2021 | 26 | |
| 16 | 2019 | 26 | |
| 17 | 2018 | 24 | |
| 18 | 2018 | 24 | |
| 19 | 2017 | 23 | |
| 20 | 2015 | 22 |
About David Wu
David Wu is a scholar working on Pathology and Forensic Medicine, Hematology, Cancer Research, Oncology and Public Health, Environmental and Occupational Health, having authored 67 papers that have together received 2.5k indexed citations. Recurring topics across this work include Lymphoma Diagnosis and Treatment (21 papers), Acute Myeloid Leukemia Research (15 papers), Cancer Genomics and Diagnostics (14 papers), Acute Lymphoblastic Leukemia research (13 papers), Chronic Lymphocytic Leukemia Research (9 papers), Chronic Myeloid Leukemia Treatments (8 papers), Immune Cell Function and Interaction (5 papers) and Genomic variations and chromosomal abnormalities (5 papers). The work is most often cited by research in Hematology (515 citations), Oncology (1.1k citations), Pathology and Forensic Medicine (496 citations), Immunology (560 citations) and Genetics (260 citations). David Wu has collaborated with scholars based in United States, South Africa and Germany. Frequent co-authors include Brent L. Wood, Jonathan R. Fromm, Harlan Robins, Min Fang, David G. Maloney, Sindhu Cherian, Anna Sherwood, Olivia Finney, Stanley R. Riddell and Cameron J. Turtle. Their work appears in journals such as Blood, Cytometry Part B Clinical Cytometry, American Journal of Clinical Pathology, Journal of Molecular Diagnostics and Biology of Blood and Marrow Transplantation.
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.