Xing Fu

5.9k total citations · 2 hit papers
94 papers, 4.2k citations indexed

About

Xing Fu is a scholar working on Molecular Biology, Physiology and Cancer Research. According to data from OpenAlex, Xing Fu has authored 94 papers receiving a total of 4.2k indexed citations (citations by other indexed papers that have themselves been cited), including 66 papers in Molecular Biology, 19 papers in Physiology and 16 papers in Cancer Research. Recurrent topics in Xing Fu's work include Adipose Tissue and Metabolism (19 papers), RNA modifications and cancer (17 papers) and RNA Research and Splicing (12 papers). Xing Fu is often cited by papers focused on Adipose Tissue and Metabolism (19 papers), RNA modifications and cancer (17 papers) and RNA Research and Splicing (12 papers). Xing Fu collaborates with scholars based in China, United States and Germany. Xing Fu's co-authors include ‬Min Du, Mei‐Jun Zhu, Jeffery D. Molkentin, Vikram Prasad, Onur Kanisicak, Hadi Khalil, Ronald J. Vagnozzi, Qiyuan Yang, Bo Wang and Jason Karch and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Nucleic Acids Research and Journal of Biological Chemistry.

In The Last Decade

Xing Fu

91 papers receiving 4.2k citations

Hit Papers

Fibroblast-specific TGF-β–Smad2/3 signaling underlies car... 2017 2026 2020 2023 2017 2018 200 400 600

Peers

Xing Fu
Comparison fields: 5 of 130
  • Molecular Biology 2.4k
  • Physiology 868
  • Cardiology and Cardiovascular Medicine 867
  • Cancer Research 546
  • Plant Science 483
Replace Sophie Rome with:
Sophie Rome France
Minerva T. Garcia-Barrio United States
Nagalingam R. Sundaresan India
Myriam Aouadi United States
Marten Szibor Germany
Thomas O. Eichmann Austria
Hui Yang China
Mingui Fu United States
Bin Xiao China
Sarah M. Nicoloro United States
Sophie Rome France View profile →
Citations per field, relative to Xing Fu
Xing Fu · 1×
Citations per year, relative to Xing Fu
Xing Fu · 1×

Countries citing papers authored by Xing Fu

Since Specialization
Citations

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

Fields of papers citing papers by Xing Fu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Xing Fu

This figure shows the co-authorship network connecting the top 25 collaborators of Xing Fu. A scholar is included among the top collaborators of Xing Fu 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 Xing Fu. Xing Fu 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
# Work Indexed citations
1 0
2 1
3 2
4 28
5 5
6 4
7 12
8 98
9 21
10 8
11 29
12 78
13 22
14 25
15 24
16 124
17 25
18 80
19 15
20 42

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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2026