Lu Dai
Impact in
- Hematology top 5%
- Chronic Myeloid Leukemia Treatments
- Cancer Research top 10%
- MicroRNA in disease regulation
- Cancer-related molecular mechanisms research
Papers in
-
- Chronic Myeloid Leukemia Treatments 4
- Platelet Disorders and Treatments 3
- Multiple Myeloma Research and Treatments 3
- Co-authors
- Mark G. Slomiany (2 shared papers)Lauren B. Tolliver (2 shared papers)Bryan P. Toole (2 shared papers)Ralph B. Arlinghaus (4 shared papers)Jiaxin Liu (3 shared papers)G. Daniel Grass (1 shared paper)Yiping Zeng (1 shared paper)Yun Wu (3 shared papers)
- Journals
- Chemical Communications (3 papers)Journal of Chromatography A (3 papers)Fish & Shellfish Immunology (2 papers)Oncotarget (2 papers)Frontiers in Genetics (2 papers)
- Partner nations
- ChinaUnited StatesSingapore
In The Last Decade
Lu Dai
69 papers receiving 1.3k citations
Peers
Comparison fields: 5 of 108
- Hematology 149
- Cancer Research 167
- Organic Chemistry 295
- Genetics 96
- Molecular Biology 535
Countries citing papers authored by Lu Dai
This map shows the geographic impact of Lu Dai'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 Lu Dai with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Lu Dai more than expected).
Fields of papers citing papers by Lu Dai
This network shows the impact of papers produced by Lu Dai. 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 Lu Dai. The network helps show where Lu Dai may publish in the future.
Co-authors
The 25 scholars most cited alongside Lu Dai, 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 75 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2009 | 100 | |
| 2 | 2009 | 87 | |
| 3 | 2014 | 82 | |
| 4 | 2013 | 68 | |
| 5 | 2015 | 57 | |
| 6 | 2010 | 50 | |
| 7 | 2014 | 49 | |
| 8 | 2012 | 48 | |
| 9 | 1996 | 44 | |
| 10 | BCR-ABL tyrosine kinase is autophosphorylated or transphosphorylates P160 BCR on tyrosine predominantly within the first BCR exon. | 1993 | 43 |
| 11 | 2021 | 39 | |
| 12 | 2009 | 37 | |
| 13 | 2014 | 35 | |
| 14 | 1997 | 34 | |
| 15 | 1999 | 32 | |
| 16 | 2009 | 31 | |
| 17 | 2013 | 30 | |
| 18 | 2016 | 27 | |
| 19 | 2021 | 27 | |
| 20 | 2021 | 22 |
About Lu Dai
Lu Dai is a scholar working on Molecular Biology, Hematology, Organic Chemistry, Immunology and Cancer Research, having authored 75 papers that have together received 1.3k indexed citations. Recurring topics across this work include Cancer-related molecular mechanisms research (6 papers), Monoclonal and Polyclonal Antibodies Research (5 papers), MicroRNA in disease regulation (5 papers), Chronic Myeloid Leukemia Treatments (4 papers), Platelet Disorders and Treatments (3 papers), Multiple Myeloma Research and Treatments (3 papers), Complement system in diseases (3 papers) and Proteoglycans and glycosaminoglycans research (3 papers). The work is most often cited by research in Hematology (149 citations), Cancer Research (167 citations), Organic Chemistry (295 citations), Genetics (96 citations) and Molecular Biology (535 citations). Lu Dai has collaborated with scholars based in China, United States and Singapore. Frequent co-authors include Mark G. Slomiany, Lauren B. Tolliver, Bryan P. Toole, Ralph B. Arlinghaus, Jiaxin Liu, G. Daniel Grass, Yiping Zeng, Yun Wu, Mei Hong and Pingping Duan. Their work appears in journals such as Chemical Communications, Journal of Chromatography A, Fish & Shellfish Immunology, Oncotarget and Frontiers in Genetics.
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.