Ying Xu

4.6k total citations
153 papers, 3.0k citations indexed

About

Ying Xu is a scholar working on Surgery, Oncology and Cancer Research. According to data from OpenAlex, Ying Xu has authored 153 papers receiving a total of 3.0k indexed citations (citations by other indexed papers that have themselves been cited), including 29 papers in Surgery, 26 papers in Oncology and 26 papers in Cancer Research. Recurrent topics in Ying Xu's work include Breast Cancer Treatment Studies (17 papers), Liver Disease Diagnosis and Treatment (16 papers) and Liver Disease and Transplantation (16 papers). Ying Xu is often cited by papers focused on Breast Cancer Treatment Studies (17 papers), Liver Disease Diagnosis and Treatment (16 papers) and Liver Disease and Transplantation (16 papers). Ying Xu collaborates with scholars based in China, United States and Japan. Ying Xu's co-authors include Jason G. Cyster, Lisa M. Kelly, João P. Pereira, Robin Lesley, Jason G. Cyster, Susan R. Schwab, Donna M. Hess, Hong‐Bing Shu, Susan L. Kalled and Mehrdad Matloubian and has published in prestigious journals such as Nature, Cell and Proceedings of the National Academy of Sciences.

In The Last Decade

Ying Xu

130 papers receiving 2.9k citations

Peers

Ying Xu
Comparison fields: 5 of 146
  • Immunology 1.4k
  • Molecular Biology 608
  • Oncology 527
  • Surgery 380
  • Cancer Research 249
Replace Kouji Izumi with:
Kouji Izumi Japan
Line Bjørge Norway
Young H. Kim United States
Hiroshi Kagamu Japan
Elizabeth C. Jury United Kingdom
Cornelius F. Waller Germany
Bruce S. Sachais United States
Christian K. Schneider Germany
Subhankar Chakraborty United States
Csaba Szalai Hungary
Kouji Izumi Japan View profile →
Citations per field, relative to Ying Xu
Ying Xu · 1×
Citations per year, relative to Ying Xu
Ying Xu · 1×

Countries citing papers authored by Ying Xu

Since Specialization
Citations

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

Fields of papers citing papers by Ying Xu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Ying Xu

This figure shows the co-authorship network connecting the top 25 collaborators of Ying Xu. A scholar is included among the top collaborators of Ying Xu 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 Ying Xu. Ying Xu 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 1
2 2
3 0
4 0
5 0
6 1
7 3
8 6
9 2
10 5
11 14
12
Data driven identification and classification of Chinese medicine syndrome types among functional dyspepsia patients: latent tree analysis (abridged secondary publication)
2
13 2
14 1
15 1
16 1
17 11
18 7
19 41
20 456

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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