Tingting Fu

458 citations
22 papers · 243 indexed · h-index 6
Topics
Direction-of-Arrival Estimation Techniques (2 papers)Advanced Proteomics Techniques and Applications (2 papers)Cancer, Hypoxia, and Metabolism (2 papers)
Partner nations
ChinaCanadaUnited States

In The Last Decade

Tingting Fu

21 papers receiving 234 citations

Peers

Tingting Fu
Comparison fields: 5 of 64
  • Genetics 80
  • Molecular Biology 68
  • Ecology, Evolution, Behavior and Systematics 63
  • Global and Planetary Change 57
  • Ecology 55
Replace Darko D. Cotoras with:
Darko D. Cotoras United States
Kai Tong China
Daniel J. MacGuigan United States
Samuel Lundqvist Sweden
Martina Pavlek Croatia
Áki J. Láruson United States
Loïs Rancilhac Germany
E. Anne Chambers United States
Peter Linder Switzerland
Juan Sebastián Moreno Colombia
Tingting Fu relative to Darko D. Cotoras United States Darko D. Cotoras's profile →
Citations per field
00.5×3.6×
Darko D. Cotoras · 1×
Citations per year

Countries citing papers authored by Tingting Fu

Since Specialization
Citations

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

Fields of papers citing papers by Tingting Fu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Tingting Fu

This figure shows the co-authorship network connecting the top 25 collaborators of Tingting Fu. A scholar is included among the top collaborators of Tingting 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 Tingting Fu. Tingting 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
#WorkIndexed citations
1 0
2 1
3 1
4 1
5 2
6 3
7 1
8 4
9 6
10 19
11 7
12 5
13 4
14 2
15 85
16 3
17 70
18 21
19 3
20 3

About Tingting Fu

Tingting Fu is a scholar working on Aging, Ecological Modeling and Physiology, having authored 22 papers that have together received 243 indexed citations. Recurring topics across this work include Direction-of-Arrival Estimation Techniques (2 papers), Advanced Proteomics Techniques and Applications (2 papers) and Cancer, Hypoxia, and Metabolism (2 papers). The work is most often cited by research in Ecological Modeling (36 citations), Ecology, Evolution, Behavior and Systematics (63 citations) and Paleontology (23 citations). Tingting Fu has collaborated with scholars based in China, Canada and United States. Frequent co-authors include Jie‐Qiong Jin, David M. Hillis, Ya‐Ping Zhang, Jing Che, Robert W. Murphy, Yanbo Sun, Wei Gao, Yan Fang, Wenjie Dong and Wei Xu. Their work appears in journals such as Proceedings of the National Academy of Sciences, Nucleic Acids Research and IEEE Transactions on Geoscience and Remote Sensing.

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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