Liwei Fang

565 total citations
31 papers, 329 citations indexed

About

Liwei Fang is a scholar working on Hematology, Genetics and Molecular Biology. According to data from OpenAlex, Liwei Fang has authored 31 papers receiving a total of 329 indexed citations (citations by other indexed papers that have themselves been cited), including 28 papers in Hematology, 19 papers in Genetics and 9 papers in Molecular Biology. Recurrent topics in Liwei Fang's work include Acute Myeloid Leukemia Research (19 papers), Myeloproliferative Neoplasms: Diagnosis and Treatment (15 papers) and Hematopoietic Stem Cell Transplantation (5 papers). Liwei Fang is often cited by papers focused on Acute Myeloid Leukemia Research (19 papers), Myeloproliferative Neoplasms: Diagnosis and Treatment (15 papers) and Hematopoietic Stem Cell Transplantation (5 papers). Liwei Fang collaborates with scholars based in China, United Kingdom and United States. Liwei Fang's co-authors include Tiejun Qin, Zefeng Xu, Lijuan Pan, Naibo Hu, Yue Zhang, Robert Peter Gale, Shiqiang Qu, Jun Shi, Zhijian Xiao and Hongli Zhang and has published in prestigious journals such as Blood, Journal of Thrombosis and Haemostasis and Oncotarget.

In The Last Decade

Liwei Fang

27 papers receiving 322 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Liwei Fang China 11 244 147 108 54 44 31 329
Shiqiang Qu China 12 295 1.2× 211 1.4× 116 1.1× 26 0.5× 71 1.6× 45 365
Carme Talarn Spain 8 206 0.8× 129 0.9× 104 1.0× 99 1.8× 42 1.0× 13 293
S. B. Marley United Kingdom 10 163 0.7× 166 1.1× 114 1.1× 57 1.1× 36 0.8× 17 364
Mridul Agrawal United States 8 187 0.8× 128 0.9× 64 0.6× 46 0.9× 30 0.7× 12 289
Eran Zimran Israel 9 156 0.6× 137 0.9× 169 1.6× 43 0.8× 35 0.8× 29 355
Ravin J. Garg United States 9 217 0.9× 200 1.4× 82 0.8× 47 0.9× 82 1.9× 11 367
Jayashree Motwani United Kingdom 9 238 1.0× 71 0.5× 72 0.7× 38 0.7× 13 0.3× 24 324
Rosa Marı́a Arana-Trejo Mexico 7 348 1.4× 193 1.3× 92 0.9× 65 1.2× 13 0.3× 12 408
Pilar Perez Abellan United Kingdom 5 203 0.8× 81 0.6× 71 0.7× 157 2.9× 42 1.0× 8 309
Marta Ubezio Italy 6 234 1.0× 181 1.2× 72 0.7× 69 1.3× 15 0.3× 10 325

Countries citing papers authored by Liwei Fang

Since Specialization
Citations

This map shows the geographic impact of Liwei Fang'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 Liwei Fang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Liwei Fang more than expected).

Fields of papers citing papers by Liwei Fang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Liwei Fang. 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 Liwei Fang. The network helps show where Liwei Fang may publish in the future.

Co-authorship network of co-authors of Liwei Fang

This figure shows the co-authorship network connecting the top 25 collaborators of Liwei Fang. A scholar is included among the top collaborators of Liwei Fang based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Liwei Fang. Liwei Fang is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Wang, Leyu, Liwei Fang, Hongxia Shi, et al.. (2024). Treatment of myelofibrosis with refractory anemia with luspatercept: a multicenter Chinese study. Annals of Hematology. 103(9). 3605–3613.
2.
Pan, Hong, Zhen Gao, Lele Zhang, et al.. (2024). Application of platelet transcriptomics for assessing treatment effectiveness and predicting long-term platelet counts recovery in aplastic anemia. Journal of Thrombosis and Haemostasis. 23(2). 692–703. 2 indexed citations
3.
Pan, Hong, Zhen Gao, Lele Zhang, et al.. (2023). High-expression of the innate-immune related gene UNC93B1 predicts inferior outcomes in acute myeloid leukemia. Frontiers in Genetics. 14. 1063227–1063227. 3 indexed citations
4.
Zhang, Lele, Yu Lian, Qian Liang, et al.. (2023). Mass cytometry analysis identifies T cell immune signature of aplastic anemia and predicts the response to cyclosporine. Annals of Hematology. 102(3). 529–539. 6 indexed citations
5.
Wang, Wenjun, Qian Liang, Hong Pan, et al.. (2022). Low expression of the metabolism-related gene SLC25A21 predicts unfavourable prognosis in patients with acute myeloid leukaemia. Frontiers in Genetics. 13. 970316–970316. 10 indexed citations
6.
Liang, Qian, Lele Zhang, Wenjun Wang, et al.. (2022). High Expression of DC-STAMP Gene Predicts Adverse Outcomes in AML. Frontiers in Genetics. 13. 876689–876689. 4 indexed citations
7.
Zhang, Lele, Zhipeng Xu, Qian Liang, et al.. (2021). Good treatment-free survival of monoclonal gammopathy of undetermined significance associated pure red cell aplasia after bortezomib plus dexamethasone. Blood Cells Molecules and Diseases. 89. 102573–102573. 3 indexed citations
8.
9.
Zhao, Jingyu, et al.. (2020). Association between IL28B Polymorphisms and Outcomes of Hepatitis B Virus Infection: A meta-analysis. BMC Medical Genetics. 21(1). 88–88. 11 indexed citations
10.
Li, Ruonan, et al.. (2020). PNH Clones for Aplastic Anemia with Immunosuppressive Therapy: A Systematic Review and Meta-Analysis. Acta Haematologica. 144(1). 34–43. 5 indexed citations
11.
12.
Qu, Shiqiang, Tiejun Qin, Zefeng Xu, et al.. (2016). Long-term outcomes of imatinib in patients with FIP1L1/PDGFRA associated chronic eosinophilic leukemia: experience of a single center in China. Oncotarget. 7(22). 33229–33236. 20 indexed citations
13.
Cui, Yajuan, Hongyan Tong, Xin Du, et al.. (2015). Impact of TET2, SRSF2, ASXL1 and SETBP1 mutations on survival of patients with chronic myelomonocytic leukemia. Experimental Hematology and Oncology. 4(1). 14–14. 29 indexed citations
14.
Wang, Jingya, Tiejun Qin, Zefeng Xu, et al.. (2015). [Long- term outcome of thalidomide and cyclosporine in patients with IPSS low/intermediate- 1 myelodysplastic syndromes].. PubMed. 36(11). 942–6. 1 indexed citations
15.
Cui, Rui, Robert Peter Gale, Zefeng Xu, et al.. (2014). Serum iron metabolism and erythropoiesis in patients with myelodysplastic syndrome not receiving RBC transfusions. Leukemia Research. 38(5). 545–550. 40 indexed citations
16.
Wang, Jingya, Robert Peter Gale, Zefeng Xu, et al.. (2014). Prognostic Impact of Splenomegaly on Survival of Chinese with Primary Myelofibrosis. Blood. 124(21). 3210–3210.
17.
Zhang, Hongli, Tiejun Qin, Zefeng Xu, et al.. (2014). [Clinical efficacy analysis of recombinant human erythropoietin in the treatment of lower-risk myelodysplastic syndromes].. PubMed. 35(1). 18–23. 1 indexed citations
18.
Wang, Jieyu, Robert Peter Gale, Zefeng Xu, et al.. (2012). TET2, ASXL1 and EZH2 mutations in Chinese with myelodysplastic syndromes. Leukemia Research. 37(3). 305–311. 34 indexed citations
19.
Cui, Rui, Robert Peter Gale, Zefeng Xu, et al.. (2012). Clinical importance of SF3B1 mutations in Chinese with myelodysplastic syndromes with ring sideroblasts. Leukemia Research. 36(11). 1428–1433. 26 indexed citations
20.
Xiao, Zhijian, Zefeng Xu, Yue Zhang, et al.. (2010). Cyclosporin A and thalidomide in patients with myelodysplastic syndromes: Results of a pilot study. Leukemia Research. 35(1). 61–65. 7 indexed citations

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.

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