Shuyi Ji

1.9k total citations · 1 hit paper
12 papers, 814 citations indexed

About

Shuyi Ji is a scholar working on Molecular Biology, Surgery and Hepatology. According to data from OpenAlex, Shuyi Ji has authored 12 papers receiving a total of 814 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Molecular Biology, 3 papers in Surgery and 3 papers in Hepatology. Recurrent topics in Shuyi Ji's work include Liver physiology and pathology (3 papers), Pancreatic function and diabetes (3 papers) and Pluripotent Stem Cells Research (2 papers). Shuyi Ji is often cited by papers focused on Liver physiology and pathology (3 papers), Pancreatic function and diabetes (3 papers) and Pluripotent Stem Cells Research (2 papers). Shuyi Ji collaborates with scholars based in China, Netherlands and United States. Shuyi Ji's co-authors include Lijian Hui, Chang‐Cheng Liu, Xin Wang, Zhiying He, Yiping Hu, Dao Xiang, Pengyu Huang, Qiang Gao, Ludi Zhang and Shuang–Jian Qiu and has published in prestigious journals such as Nature, Proceedings of the National Academy of Sciences and Gastroenterology.

In The Last Decade

Shuyi Ji

11 papers receiving 805 citations

Hit Papers

Induction of functional hepatocyte-like cells from mouse ... 2011 2026 2016 2021 2011 200 400 600

Peers

Shuyi Ji
Comparison fields: 5 of 73
  • Molecular Biology 616
  • Surgery 259
  • Hepatology 200
  • Biomedical Engineering 105
  • Physiology 62
Replace Zoë Hewitt with:
Zoë Hewitt United Kingdom
Thomas Touboul France
Lakshmi Rambhatla United States
Laura Broutier France
Luigi Aloia Italy
Uyunbilig Borjigin China
Adrián Álvarez-Varela Spain
Hiroaki Ayabe Japan
Robert Fordham United Kingdom
Dustin J. Flanagan Australia
Zoë Hewitt United Kingdom View profile →
Citations per field, relative to Shuyi Ji
Shuyi Ji · 1×
Citations per year, relative to Shuyi Ji
Shuyi Ji · 1×

Countries citing papers authored by Shuyi Ji

Since Specialization
Citations

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

Fields of papers citing papers by Shuyi Ji

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Shuyi Ji

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

All Works

12 of 12 papers shown
# Work Indexed citations
1 0
2 3
3 5
4 27
5 6
6 10
7 8
8 60
9 18
10 3
11 16
12
Induction of functional hepatocyte-like cells from mouse fibroblasts by defined factors breakdown →
658

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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