Zhangfei Shen

778 total citations
25 papers, 439 citations indexed

About

Zhangfei Shen is a scholar working on Molecular Biology, Cellular and Molecular Neuroscience and Immunology. According to data from OpenAlex, Zhangfei Shen has authored 25 papers receiving a total of 439 indexed citations (citations by other indexed papers that have themselves been cited), including 18 papers in Molecular Biology, 8 papers in Cellular and Molecular Neuroscience and 5 papers in Immunology. Recurrent topics in Zhangfei Shen's work include Neurobiology and Insect Physiology Research (7 papers), RNA modifications and cancer (4 papers) and CRISPR and Genetic Engineering (4 papers). Zhangfei Shen is often cited by papers focused on Neurobiology and Insect Physiology Research (7 papers), RNA modifications and cancer (4 papers) and CRISPR and Genetic Engineering (4 papers). Zhangfei Shen collaborates with scholars based in United States, China and Germany. Zhangfei Shen's co-authors include Tian‐Min Fu, Xiaoyuan Yang, Naiming Zhou, Yajie Chen, Liangen Shi, Hongqing Xie, Xiaotong Li, Jeffrey R. Holt, Chen Shen and Kotaro Nakanishi and has published in prestigious journals such as Nature, Science and Cell.

In The Last Decade

Zhangfei Shen

24 papers receiving 435 citations

Peers

Zhangfei Shen
Comparison fields: 5 of 75
  • Molecular Biology 262
  • Cellular and Molecular Neuroscience 66
  • Ecology 64
  • Epidemiology 52
  • Genetics 47
Replace Olga Vitavska with:
Olga Vitavska Germany
Raul Salinas United States
Chang‐Su Lim United States
Saurabh G. Roy United States
Sarah J. Medina Canada
David Bauer United States
Yufang Chao United States
Kenzi Oshima Japan
May T. Aung-Htut Australia
Alicia M. Celotto United States
Olga Vitavska Germany View profile →
Citations per field, relative to Zhangfei Shen
Zhangfei Shen · 1×
Citations per year, relative to Zhangfei Shen
Zhangfei Shen · 1×

Countries citing papers authored by Zhangfei Shen

Since Specialization
Citations

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

Fields of papers citing papers by Zhangfei Shen

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Zhangfei Shen

This figure shows the co-authorship network connecting the top 25 collaborators of Zhangfei Shen. A scholar is included among the top collaborators of Zhangfei Shen 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 Zhangfei Shen. Zhangfei Shen 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 4
2 1
3 23
4 11
5 11
6 20
7 4
8 32
9 49
10 35
11 53
12 21
13 4
14 38
15 16
16 4
17 35
18 12
19 13
20 8

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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