Ying Lu
Impact in
- Hematology top 10%
- Acute Myeloid Leukemia Research
- Hematopoietic Stem Cell Transplantation
- Oncology top 10%
- CAR-T cell therapy research
- Drug Transport and Resistance Mechanisms
Papers in
- Hematology 24
- Acute Myeloid Leukemia Research 17
- Hematopoietic Stem Cell Transplantation 6
- Chronic Myeloid Leukemia Treatments 6
- Multiple Myeloma Research and Treatments 4
- Co-authors
- Mohammed Kashani–Sabet (3 shared papers)Kevin J. Scanlon (3 shared papers)Endi Wang (3 shared papers)Wei Chen (2 shared papers)Juying Wei (2 shared papers)Zheming Lu (2 shared papers)Zhilu Chen (2 shared papers)Qunyi Guo (2 shared papers)
- Journals
- Blood (7 papers)Annals of Hematology (4 papers)American Journal of Hematology (2 papers)iScience (2 papers)Acta Haematologica (2 papers)
- Partner nations
- ChinaUnited StatesSweden
In The Last Decade
Ying Lu
54 papers receiving 550 citations
Peers
Comparison fields: 5 of 71
- Hematology 114
- Oncology 210
- Genetics 37
- Immunology 74
- Pathology and Forensic Medicine 52
Countries citing papers authored by Ying Lu
This map shows the geographic impact of Ying Lu'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 Ying Lu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Ying Lu more than expected).
Fields of papers citing papers by Ying Lu
This network shows the impact of papers produced by Ying Lu. 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 Ying Lu. The network helps show where Ying Lu may publish in the future.
Co-authors
The 25 scholars most cited alongside Ying Lu, 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 60 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2020 | 110 | |
| 2 | Detection of drug resistance in human tumors by in vitro enzymatic amplification. | 1988 | 34 |
| 3 | 1990 | 33 | |
| 4 | 2009 | 31 | |
| 5 | 1988 | 28 | |
| 6 | 2017 | 28 | |
| 7 | 2020 | 26 | |
| 8 | 2022 | 26 | |
| 9 | 2010 | 22 | |
| 10 | 2009 | 18 | |
| 11 | 2020 | 16 | |
| 12 | 2010 | 15 | |
| 13 | 2020 | 14 | |
| 14 | 2020 | 14 | |
| 15 | 2019 | 14 | |
| 16 | 2022 | 13 | |
| 17 | 2020 | 10 | |
| 18 | 2022 | 10 | |
| 19 | 2004 | 9 | |
| 20 | 2019 | 7 |
About Ying Lu
Ying Lu is a scholar working on Hematology, Molecular Biology, Oncology, Public Health, Environmental and Occupational Health and Genetics, having authored 60 papers that have together received 556 indexed citations. Recurring topics across this work include Acute Myeloid Leukemia Research (17 papers), Acute Lymphoblastic Leukemia research (7 papers), Hematopoietic Stem Cell Transplantation (6 papers), Chronic Myeloid Leukemia Treatments (6 papers), CAR-T cell therapy research (5 papers), Myeloproliferative Neoplasms: Diagnosis and Treatment (4 papers), Immune cells in cancer (4 papers) and Multiple Myeloma Research and Treatments (4 papers). The work is most often cited by research in Hematology (114 citations), Oncology (210 citations), Genetics (37 citations), Immunology (74 citations) and Pathology and Forensic Medicine (52 citations). Ying Lu has collaborated with scholars based in China, United States and Sweden. Frequent co-authors include Mohammed Kashani–Sabet, Kevin J. Scanlon, Endi Wang, Wei Chen, Juying Wei, Zheming Lu, Zhilu Chen, Qunyi Guo, Chaoting Zhang and Wenbin Qian. Their work appears in journals such as Blood, Annals of Hematology, American Journal of Hematology, iScience and Acta Haematologica.
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.