Bin Fu

930 citations
29 papers · 647 · h-index 14

Impact in

  • Hematology top 5%
    • Acute Myeloid Leukemia Research
    • Chronic Myeloid Leukemia Treatments
  • Genetics top 5%
    • Myeloproliferative Neoplasms: Diagnosis and Treatment

Papers in

Bin Fu

28 papers receiving 642 citations

Peers

Bin Fu
Comparison fields: 5 of 67
  • Hematology 249
  • Genetics 163
  • Cancer Research 136
  • Molecular Biology 314
  • Biological Psychiatry 11
Replace Mariko Takenokuchi with:
Mariko Takenokuchi Japan
Anna Rogers United States
Sida Zhao China
Othman Al‐Sawaf Germany
Jayna J. Mistry United Kingdom
Harold K. Elias United States
Lin Tang China
Valeria Bafunno Italy
Yanjie Xu China
Bin Fu relative to Mariko Takenokuchi Japan Mariko Takenokuchi's profile →
Citations per field
00.5×5.5×
Mariko Takenokuchi · 1×
Citations per year

Countries citing papers authored by Bin Fu

Since Specialization
Citations

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

Fields of papers citing papers by Bin Fu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Bin Fu, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Bin Fu Line = papers co-authored together Bin Fu links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 29 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2019106
2 201488
3 202173
4 201460
5 201341
6 201537
7 202029
8 201924
9 201620
10 201519
11 201318
12 201718
13 201917
14 202114
15 202013
16 202411
17 201911
18 20139
19 20109
20 20178

About Bin Fu

Bin Fu is a scholar working on Molecular Biology, Hematology, Oncology, Surgery and Cancer Research, having authored 29 papers that have together received 647 indexed citations. Recurring topics across this work include Acute Myeloid Leukemia Research (8 papers), Myeloproliferative Neoplasms: Diagnosis and Treatment (3 papers), Histiocytic Disorders and Treatments (3 papers), Liver physiology and pathology (2 papers), Retinoids in leukemia and cellular processes (2 papers), Cancer, Stress, Anesthesia, and Immune Response (2 papers), Cancer Immunotherapy and Biomarkers (2 papers) and Immune cells in cancer (2 papers). The work is most often cited by research in Hematology (249 citations), Genetics (163 citations), Cancer Research (136 citations), Molecular Biology (314 citations) and Biological Psychiatry (11 citations). Bin Fu has collaborated with scholars based in China, United States and United Kingdom. Frequent co-authors include L. Jeffrey Medeiros, Maitrayee Goswami, Sa A. Wang, Lei Jiang, Qingbai Liu, Meng Li, Guilin Tang, Guillermo Garcia‐Manero, Mengdi Yang and Rong Hu. Their work appears in journals such as Biochemical and Biophysical Research Communications, British Journal of Haematology, Frontiers in Aging Neuroscience, Leukemia Research and BMC Pulmonary Medicine.

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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