Xiaodong Fu

87 papers receiving 2.2k citations

Peers

Xiaodong Fu
Comparison fields: 5 of 111
  • Endocrinology, Diabetes and Metabolism 386
  • Immunology and Allergy 134
  • Genetics 583
  • Biochemistry 151
  • Cancer Research 310
Replace Takeshi Marumo with:
Takeshi Marumo Japan
Ken L. Chambliss United States
Yiu-Fai Chen United States
Delbert G. Gillespie United States
Tuula Kiviluoto Finland
Anuradha Vivekanandan‐Giri United States
Rama Pai United States
Masatoshi Kikuchi Japan
Nicola Perrotti Italy
Robert F. Spurney United States
Xiaodong Fu relative to Takeshi Marumo Japan Takeshi Marumo's profile →
Citations per field
00.5×
Takeshi Marumo · 1×
Citations per year

Countries citing papers authored by Xiaodong Fu

Since Specialization
Citations

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

Fields of papers citing papers by Xiaodong Fu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Xiaodong 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 Xiaodong Fu Line = papers co-authored together Xiaodong Fu links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 92 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2006158
2 2012101
3 201080
4 200876
5 200976
6 201071
7 200865
8 201964
9 201763
10 201161
11 201853
12 201053
13 201250
14 201949
15 201748
16 202042
17 201841
18 202040
19 201239
20 200739

About Xiaodong Fu

Xiaodong Fu is a scholar working on Molecular Biology, Genetics, Oncology, Surgery and Cancer Research, having authored 92 papers that have together received 2.2k indexed citations. Recurring topics across this work include Estrogen and related hormone effects (30 papers), Nitric Oxide and Endothelin Effects (10 papers), Menopause: Health Impacts and Treatments (7 papers), Cytokine Signaling Pathways and Interactions (6 papers), Angiogenesis and VEGF in Cancer (6 papers), Cell Adhesion Molecules Research (6 papers), MicroRNA in disease regulation (6 papers) and Cancer-related molecular mechanisms research (6 papers). The work is most often cited by research in Endocrinology, Diabetes and Metabolism (386 citations), Immunology and Allergy (134 citations), Genetics (583 citations), Biochemistry (151 citations) and Cancer Research (310 citations). Xiaodong Fu has collaborated with scholars based in China, Italy and United States. Frequent co-authors include Tommaso Simoncini, Maria Silvia Giretti, Tinghuai Wang, Marina Inés Flamini, Angel Matías Sanchez, Andrea Riccardo Genazzani, Lorenzo Goglia, Xiaosa Li, Silvia Garibaldi and Dongxing Zhu. Their work appears in journals such as Vascular Pharmacology, Molecular Human Reproduction, Cardiovascular Research, Molecular Biology Reports and PLoS ONE.

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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