Xiaodan Fu

423 citations
30 papers · 202 · h-index 8

Impact in

Papers in

Xiaodan Fu

28 papers receiving 198 citations

Peers

Xiaodan Fu
Comparison fields: 5 of 58
  • Cancer Research 77
  • Nephrology 14
  • Molecular Biology 98
  • Reproductive Medicine 10
  • Oncology 30
Replace Takuya Kumazawa with:
Takuya Kumazawa Japan
Jingyu Ma China
Л. П. Менделеева Russia
Zorka Inić Serbia
Rupert Faraway United Kingdom
Jan C. Drooger Netherlands
Xiaohui Zhai China
Yi Qu China
Xiaodan Fu relative to Takuya Kumazawa Japan Takuya Kumazawa's profile →
Citations per field
00.5×2.7×
Takuya Kumazawa · 1×
Citations per year

Countries citing papers authored by Xiaodan Fu

Since Specialization
Citations

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

Fields of papers citing papers by Xiaodan Fu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 30 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201647
2 201921
3 202419
4 201813
5 201512
6 202210
7 20227
8 20207
9 20256
10 20226
11 20216
12 20175
13 20235
14 20235
15 20215
16
Gallstones and their chemical types in relation to serum lipids and apolipoprotein levels.
19975
17
[Significance of P504s in distinction between solid pseudopapillary tumor of pancreas and pancreatic neuroendocrine tumors].
20154
18 20233
19 20143
20 20242

About Xiaodan Fu

Xiaodan Fu is a scholar working on Molecular Biology, Pulmonary and Respiratory Medicine, Cancer Research, Immunology and Oncology, having authored 30 papers that have together received 202 indexed citations. Recurring topics across this work include Cancer-related molecular mechanisms research (6 papers), RNA modifications and cancer (5 papers), Ferroptosis and cancer prognosis (5 papers), Endometrial and Cervical Cancer Treatments (2 papers), Circular RNAs in diseases (2 papers), Cancer-related gene regulation (2 papers), Gamma-ray bursts and supernovae (2 papers) and Immune cells in cancer (2 papers). The work is most often cited by research in Cancer Research (77 citations), Nephrology (14 citations), Molecular Biology (98 citations), Reproductive Medicine (10 citations) and Oncology (30 citations). Xiaodan Fu has collaborated with scholars based in China, United States and United Kingdom. Frequent co-authors include Yimin Li, Qihui Wu, Jiaxin Liu, Ruotong Tian, Chunlin Ou, Weilu Kuang, Juanni Li, Wei Guo, Wenjuan Zhou and Jifang Wen. Their work appears in journals such as Frontiers in Immunology, Diagnostic Pathology, Frontiers in Molecular Biosciences, iScience and 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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