Fan Tu

1.5k citations
24 papers · 550 indexed · h-index 11

Impact in

  • Cell Biology top 10%
    • Microtubule and mitosis dynamics
    • Protist diversity and phylogeny
    • Renal and related cancers
    • Bioinformatics and Genomic Networks
    • RNA Research and Splicing
    • RNA modifications and cancer
    • RNA and protein synthesis mechanisms

Papers in

Fan Tu

22 papers receiving 548 citations

Peers

Fan Tu
Comparison fields: 5 of 81
  • Cell Biology 138
  • Molecular Biology 401
  • Genetics 155
  • Aging 6
  • Spectroscopy 42
Replace Kaige Yan with:
Kaige Yan China
Verena Dederer Germany
Irina M. Armean United Kingdom
Daniel P. Farrell United States
Jayasha Shandilya India
Zuanning Yuan United States
David Rattray Canada
Amy L. Robertson Australia
Xiangdong Zheng China
Julie M. Sahalie United States
Fan Tu relative to Kaige Yan China Kaige Yan's profile →
Citations per field
00.5×
Kaige Yan · 1×
Citations per year

Countries citing papers authored by Fan Tu

Since Specialization
Citations

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

Fields of papers citing papers by Fan Tu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 24 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2017127
2 201496
3 201664
4 201852
5 201947
6 201734
7 201825
8 202222
9 202219
10 202113
11 201110
12 20227
13 20236
14 20235
15 20235
16 20214
17 20214
18 20233
19 20253
20 20252

About Fan Tu

Fan Tu is a scholar working on Microbiology, Endocrinology, Cell Biology, Genetics and Molecular Medicine, having authored 24 papers that have together received 550 indexed citations. Recurring topics across this work include Genetic and Kidney Cyst Diseases (5 papers), Immune Response and Inflammation (3 papers), Antimicrobial Peptides and Activities (3 papers), Advanced Fiber Optic Sensors (2 papers), Renal and related cancers (2 papers), RNA Research and Splicing (2 papers), Liver Disease Diagnosis and Treatment (2 papers) and Cellular Mechanics and Interactions (2 papers). The work is most often cited by research in Cell Biology (138 citations), Molecular Biology (401 citations), Genetics (155 citations), Aging (6 citations) and Spectroscopy (42 citations). Fan Tu has collaborated with scholars based in China, United States and Australia. Frequent co-authors include John B. Wallingford, Edward M. Marcotte, Jakub Sedzinski, Chanjae Lee, Édouard Hannezo, Yun Ma, Maté Biro, Kevin Drew, Blake Borgeson and Claire D. McWhite. Their work appears in journals such as Journal of Cell Science, eLife, Differentiation, Scientific Reports and Frontiers in Microbiology.

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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