Yining Ye

31 papers receiving 685 citations

Peers

Yining Ye
Comparison fields: 5 of 101
  • Statistics and Probability 155
  • Oncology 235
  • Endocrine and Autonomic Systems 57
  • Immunology 97
  • Pulmonary and Respiratory Medicine 132
Replace Jianchang Lin with:
Jianchang Lin United States
Haocheng Li Canada
Serena G. Liao United States
Lars Beckmann Germany
Peter Salzman United States
Min Jin Ha United States
H. Rauschecker Germany
Jiayi Tong United States
Shengjie Yang China
Hoang Q. Nguyen United States
Yining Ye relative to Jianchang Lin United States Jianchang Lin's profile →
Citations per field
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Citations per year

Countries citing papers authored by Yining Ye

Since Specialization
Citations

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

Fields of papers citing papers by Yining Ye

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Yining Ye, 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 Yining Ye Line = papers co-authored together Yining Ye links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 32 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2007107
2 200893
3 201391
4 201362
5 200551
6 200944
7 201436
8 201235
9 201327
10 202416
11 200716
12 201916
13 201915
14 202413
15 200613
16 201211
17 20077
18 20237
19 20197
20 20145

About Yining Ye

Yining Ye is a scholar working on General Engineering, Statistics and Probability, Health Information Management, Oncology and Information Systems and Management, having authored 32 papers that have together received 703 indexed citations. Recurring topics across this work include Fibroblast Growth Factor Research (9 papers), Lung Cancer Treatments and Mutations (5 papers), CAR-T cell therapy research (4 papers), Health Systems, Economic Evaluations, Quality of Life (3 papers), Peptidase Inhibition and Analysis (3 papers), Cholangiocarcinoma and Gallbladder Cancer Studies (3 papers), Viral Infectious Diseases and Gene Expression in Insects (3 papers) and Cancer Treatment and Pharmacology (2 papers). The work is most often cited by research in Statistics and Probability (155 citations), Oncology (235 citations), Endocrine and Autonomic Systems (57 citations), Immunology (97 citations) and Pulmonary and Respiratory Medicine (132 citations). Yining Ye has collaborated with scholars based in United States, Spain and Germany. Frequent co-authors include Douglas E. Schaubel, John D. Kalbfleisch, Jason Chesney, Robert S. Coffin, Robert Hans Ingemar Andtbacka, Howard L. Kaufman, Thomas Amatruda, Neil Senzer, Igor Puzanov and Keith A. Delman. Their work appears in journals such as Journal of Clinical Oncology, Biometrics, Journal of Substance Abuse Treatment, Cancer Research and Buildings.

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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