Ying Lu
Impact in
- Cancer Research top 10%
- NF-κB Signaling Pathways
- Cancer, Hypoxia, and Metabolism
- Hematology top 5%
- Acute Myeloid Leukemia Research
Papers in
-
- Ubiquitin and proteasome pathways 3
- Retinoids in leukemia and cellular processes 3
- RNA Research and Splicing 3
- Hematology 12
- Acute Myeloid Leukemia Research 8
- Chronic Myeloid Leukemia Treatments 5
- Co-authors
- C.H. Arrowsmith (1 shared paper)Gwan‐Su Yi (1 shared paper)Frans A. A. Mulder (1 shared paper)Ayeda Ayed (1 shared paper)Lewis E. Kay (1 shared paper)Sushil K. Thukral (3 shared papers)Guoqiang Chen (8 shared papers)Luc E. M. Marengère (1 shared paper)
- Journals
- Cell Death and Disease (4 papers)Proceedings of the National Academy of Sciences (2 papers)Cancer Letters (1 paper)Experimental Hematology (1 paper)Journal of Biosciences (1 paper)
- Partner nations
- ChinaUnited StatesThailand
In The Last Decade
Ying Lu
56 papers receiving 1.1k citations
Peers
Comparison fields: 5 of 105
- Cancer Research 197
- Hematology 149
- Oncology 258
- Molecular Biology 699
- Immunology 120
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 56 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2001 | 233 | |
| 2 | 1997 | 88 | |
| 3 | 2012 | 85 | |
| 4 | 2021 | 66 | |
| 5 | 2003 | 63 | |
| 6 | 2019 | 57 | |
| 7 | 1995 | 40 | |
| 8 | 2021 | 30 | |
| 9 | 2006 | 29 | |
| 10 | 2016 | 28 | |
| 11 | 2006 | 28 | |
| 12 | 2021 | 27 | |
| 13 | 2016 | 26 | |
| 14 | 2017 | 26 | |
| 15 | 2019 | 24 | |
| 16 | 2016 | 24 | |
| 17 | 2018 | 20 | |
| 18 | 2011 | 19 | |
| 19 | 2014 | 17 | |
| 20 | 2017 | 17 |
About Ying Lu
Ying Lu is a scholar working on Molecular Biology, Hematology, Oncology, Cancer Research and Surgery, having authored 56 papers that have together received 1.1k indexed citations. Recurring topics across this work include Acute Myeloid Leukemia Research (8 papers), Chronic Myeloid Leukemia Treatments (5 papers), Cancer, Hypoxia, and Metabolism (5 papers), Cancer-related Molecular Pathways (4 papers), Cytomegalovirus and herpesvirus research (4 papers), Ubiquitin and proteasome pathways (3 papers), Retinoids in leukemia and cellular processes (3 papers) and RNA Research and Splicing (3 papers). The work is most often cited by research in Cancer Research (197 citations), Hematology (149 citations), Oncology (258 citations), Molecular Biology (699 citations) and Immunology (120 citations). Ying Lu has collaborated with scholars based in China, United States and Thailand. Frequent co-authors include C.H. Arrowsmith, Gwan‐Su Yi, Frans A. A. Mulder, Ayeda Ayed, Lewis E. Kay, Sushil K. Thukral, Guoqiang Chen, Luc E. M. Marengère, Tak W. Mak and Louis-Martin Boucher. Their work appears in journals such as Cell Death and Disease, Proceedings of the National Academy of Sciences, Cancer Letters, Experimental Hematology and Journal of Biosciences.
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.