Yunying Shi

4.6k citations
110 papers · 3.6k indexed · 1 hit paper · h-index 28

Yunying Shi

103 papers receiving 3.5k citations

Hit Papers

Adipose-derived adult stromal cells heal critical-size mo...7292004202620112018200400600

Peers

Yunying Shi
Comparison fields: 5 of 153
  • Transplantation 385
  • Genetics 718
  • Urology 196
  • Surgery 1.0k
  • Rheumatology 334
Replace Linda Chen with:
Linda Chen United States
Laurence Seidel Belgium
Peter R. Mertens Germany
Andrzej Pawlik Poland
William K. Vaughn United States
Hermann Reichenspurner Germany
Alok Srivastava India
Tomoaki Taguchi Japan
Mark L. Barr United States
Leif Jansson Sweden
Yunying Shi relative to Linda Chen United States Linda Chen's profile →
Citations per field
00.5×
Linda Chen · 1×
Citations per year

Countries citing papers authored by Yunying Shi

Since Specialization
Citations

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

Fields of papers citing papers by Yunying Shi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

The 25 scholars most cited alongside Yunying Shi, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Yunying Shi Line = papers co-authored together Yunying Shi links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20250
2 20243
3 20242
4 20240
5 20234
6 20232
7
Food Literacy and Its Associated Factors in Non-Dialysis Patients with Chronic Kidney Disease in China: A Cross-Sectional Study
20223
8 20211
9 20191
10 201920
11 20180
12 201611
13 201510
14 201523
15 201413
16 2012221
17 201233
18 201218
19 201111
20 199965

About Yunying Shi

Yunying Shi is a scholar working on Transplantation, Nephrology and Hepatology, having authored 110 papers that have together received 3.6k indexed citations. Recurring topics across this work include Renal Transplantation Outcomes and Treatments (23 papers), Immune Cell Function and Interaction (10 papers), T-cell and B-cell Immunology (10 papers), Pharmacological Effects and Toxicity Studies (9 papers), Organ Transplantation Techniques and Outcomes (7 papers), Drug Transport and Resistance Mechanisms (5 papers), Rheumatoid Arthritis Research and Therapies (5 papers) and Chronic Kidney Disease and Diabetes (5 papers). The work is most often cited by research in Transplantation (385 citations), Genetics (718 citations) and Urology (196 citations). Yunying Shi has collaborated with scholars based in China, United States and Netherlands. Frequent co-authors include Michael T. Longaker, Lanlan Wang, Natalina Quarto, Benjamin M. Wu, C Marí, Catherine M. Cowan, Oliver Aalami, Christopher H. Contag, Yu‐Fen Chou and Zhuochun Huang. Their work appears in journals such as Proceedings of the National Academy of Sciences, SHILAP Revista de lepidopterología and Nature Biotechnology.

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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