Suxia Geng
Impact in
- Genetics top 2%
- Mesenchymal stem cell research
- Hematology top 5%
- Hematopoietic Stem Cell Transplantation
- Acute Myeloid Leukemia Research
Papers in
- Hematology 30
- Acute Myeloid Leukemia Research 20
- Hematopoietic Stem Cell Transplantation 8
- Chronic Myeloid Leukemia Treatments 6
- Genetics 14
- Mesenchymal stem cell research 7
- Co-authors
- Jianyu Weng (43 shared papers)Xin Du (32 shared papers)Peilong Lai (32 shared papers)Suijing Wu (12 shared papers)Yangqiu Li (17 shared papers)Chengxin Deng (20 shared papers)Lijian Yang (14 shared papers)Xin Huang (20 shared papers)
In The Last Decade
Suxia Geng
57 papers receiving 1.1k citations
Peers
Comparison fields: 5 of 70
- Genetics 345
- Hematology 322
- Immunology 282
- Cancer Research 144
- Transplantation 17
Countries citing papers authored by Suxia Geng
This map shows the geographic impact of Suxia Geng'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 Suxia Geng with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Suxia Geng more than expected).
Fields of papers citing papers by Suxia Geng
This network shows the impact of papers produced by Suxia Geng. 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 Suxia Geng. The network helps show where Suxia Geng may publish in the future.
Co-authors
The 25 scholars most cited alongside Suxia Geng, 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 59 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2010 | 193 | |
| 2 | 2018 | 149 | |
| 3 | 2012 | 73 | |
| 4 | 2019 | 47 | |
| 5 | 2020 | 46 | |
| 6 | 2007 | 34 | |
| 7 | 2022 | 31 | |
| 8 | 2010 | 29 | |
| 9 | 2014 | 27 | |
| 10 | 2011 | 25 | |
| 11 | 2008 | 25 | |
| 12 | 2011 | 21 | |
| 13 | 2005 | 21 | |
| 14 | 2012 | 20 | |
| 15 | 2010 | 20 | |
| 16 | 2022 | 19 | |
| 17 | 2023 | 18 | |
| 18 | 2021 | 17 | |
| 19 | Co-occurrence of RUNX1 and ASXL1 mutations underlie poor response and outcome for MDS patients treated with HMAs. | 2019 | 16 |
| 20 | 2011 | 15 |
About Suxia Geng
Suxia Geng is a scholar working on Hematology, Genetics, Immunology, Oncology and Public Health, Environmental and Occupational Health, having authored 59 papers that have together received 1.1k indexed citations. Recurring topics across this work include Acute Myeloid Leukemia Research (20 papers), Immune Cell Function and Interaction (11 papers), Hematopoietic Stem Cell Transplantation (8 papers), Acute Lymphoblastic Leukemia research (7 papers), T-cell and B-cell Immunology (7 papers), Mesenchymal stem cell research (7 papers), CAR-T cell therapy research (6 papers) and Chronic Myeloid Leukemia Treatments (6 papers). The work is most often cited by research in Genetics (345 citations), Hematology (322 citations), Immunology (282 citations), Cancer Research (144 citations) and Transplantation (17 citations). Suxia Geng has collaborated with scholars based in China, Germany and Poland. Frequent co-authors include Jianyu Weng, Xin Du, Peilong Lai, Suijing Wu, Yangqiu Li, Chengxin Deng, Lijian Yang, Xin Huang, Shaohua Chen and Yulian Wang. Their work appears in journals such as Journal of Hematology & Oncology, International Immunopharmacology, Blood, DNA and Cell Biology and Leukemia Research.
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.