Shanshan Jin

2.7k total citations · 3 hit papers
61 papers, 2.0k citations indexed

About

Shanshan Jin is a scholar working on Molecular Biology, Immunology and Biomaterials. According to data from OpenAlex, Shanshan Jin has authored 61 papers receiving a total of 2.0k indexed citations (citations by other indexed papers that have themselves been cited), including 28 papers in Molecular Biology, 12 papers in Immunology and 11 papers in Biomaterials. Recurrent topics in Shanshan Jin's work include Wound Healing and Treatments (8 papers), Tendon Structure and Treatment (5 papers) and Electrospun Nanofibers in Biomedical Applications (5 papers). Shanshan Jin is often cited by papers focused on Wound Healing and Treatments (8 papers), Tendon Structure and Treatment (5 papers) and Electrospun Nanofibers in Biomedical Applications (5 papers). Shanshan Jin collaborates with scholars based in China, United States and United Arab Emirates. Shanshan Jin's co-authors include Yu Wang, Yan Liu, Danqing He, Dan Luo, Lisha Zhu, Yan-Heng Zhou, Zixin Li, Cun‐Yu Wang, Min Yu and Bo Guan and has published in prestigious journals such as Advanced Materials, Nature Communications and Journal of Clinical Oncology.

In The Last Decade

Shanshan Jin

55 papers receiving 2.0k citations

Hit Papers

A Biomimetic Hierarchical Nanointerface Orchestrates Macr... 2019 2026 2021 2023 2019 2022 2023 100 200 300

Peers

Shanshan Jin
Comparison fields: 5 of 129
  • Molecular Biology 786
  • Biomedical Engineering 523
  • Immunology 258
  • Biomaterials 253
  • Surgery 236
Replace Gaoran Ge with:
Gaoran Ge China
Janak L. Pathak China
Andreas Kampmann Germany
Daozhang Cai China
Wataru Ariyoshi Japan
Mari T. Kaartinen Canada
Ning Hu China
Gisela Rodrigues da Silva Sasso Brazil
Gaoran Ge China View profile →
Citations per field, relative to Shanshan Jin
Shanshan Jin · 1×
Citations per year, relative to Shanshan Jin
Shanshan Jin · 1×

Countries citing papers authored by Shanshan Jin

Since Specialization
Citations

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

Fields of papers citing papers by Shanshan Jin

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Shanshan Jin

This figure shows the co-authorship network connecting the top 25 collaborators of Shanshan Jin. A scholar is included among the top collaborators of Shanshan Jin 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 Shanshan Jin. Shanshan Jin 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 2
2 0
3 14
4 2
5 26
6 1
7 46
8 3
9 12
10 22
11 84
12 105
13 6
14 5
15 31
16 5
17 15
18 3
19 19
20 28

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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