Xiaojun Shi

978 citations
19 papers · 718 indexed · h-index 12
Topics
Axon Guidance and Neuronal Signaling (7 papers)Lipid Membrane Structure and Behavior (4 papers)Hippo pathway signaling and YAP/TAZ (3 papers)
Partner nations
United StatesChina

In The Last Decade

Xiaojun Shi

18 papers receiving 711 citations

Peers

Xiaojun Shi
Comparison fields: 5 of 71
  • Molecular Biology 359
  • Electrical and Electronic Engineering 233
  • Materials Chemistry 172
  • Cellular and Molecular Neuroscience 129
  • Cell Biology 80
Replace Ethan S. Karp with:
Ethan S. Karp United States
Doris Höglinger Germany
Mairi E. Sandison United Kingdom
Jumi Park South Korea
Martin Stöckl Germany
Hsiung‐Lin Tu Taiwan
Myeong‐Gyun Kang South Korea
Khanh Do United States
Franck Delavoie France
Jin Zou United States
Xiaojun Shi relative to Ethan S. Karp United States Ethan S. Karp's profile →
Citations per field
00.5×
Ethan S. Karp · 1×
Citations per year

Countries citing papers authored by Xiaojun Shi

Since Specialization
Citations

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

Fields of papers citing papers by Xiaojun Shi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Xiaojun Shi

This figure shows the co-authorship network connecting the top 25 collaborators of Xiaojun Shi. A scholar is included among the top collaborators of Xiaojun Shi 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 Xiaojun Shi. Xiaojun Shi is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

19 of 19 papers shown
#WorkIndexed citations
1 22
2 1
3 127
4 32
5 31
6 35
7 1
8 39
9 13
10 20
11 135
12 1
13 0
14 19
15 111
16 117
17 9
18 4
19
Establishment and optimization of mice brain ischemia Reperfusion model
1

About Xiaojun Shi

Xiaojun Shi is a scholar working on Cellular and Molecular Neuroscience, Biophysics and Cell Biology, having authored 19 papers that have together received 718 indexed citations. Recurring topics across this work include Axon Guidance and Neuronal Signaling (7 papers), Lipid Membrane Structure and Behavior (4 papers) and Hippo pathway signaling and YAP/TAZ (3 papers). The work is most often cited by research in Biophysics (52 citations), Cellular and Molecular Neuroscience (129 citations) and Polymers and Plastics (76 citations). Xiaojun Shi has collaborated with scholars based in United States and China. Frequent co-authors include Adam W. Smith, Xiong Gong, Chao Yi, Yifan Ge, Megan J. Kaliszewski, Luke H. Chao, Sivakumar Boopathy, Chang Liu, Kai Wang and Alan J. Heeger. Their work appears in journals such as Science, Accounts of Chemical Research and Advanced Functional Materials.

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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