Pei Ye

924 citations
50 papers · 601 · h-index 16

Impact in

Papers in

Pei Ye

44 papers receiving 589 citations

Peers

Pei Ye
Comparison fields: 5 of 112
  • Applied Psychology 45
  • Periodontics 36
  • Immunology 93
  • Cancer Research 64
  • Molecular Biology 218
Replace Hsin‐Yi Chen with:
Hsin‐Yi Chen Taiwan
Bingyan Wang China
Andreas Lackner Austria
Chester Ni United States
Heather A. Parker New Zealand
Haijun Fu China
James J. Thompson United States
Crescenzio Gallo Italy
Xi Shen China
Alberto Fucarino Italy
Pei Ye relative to Hsin‐Yi Chen Taiwan Hsin‐Yi Chen's profile →
Citations per field
00.5×
Hsin‐Yi Chen · 1×
Citations per year

Countries citing papers authored by Pei Ye

Since Specialization
Citations

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

Fields of papers citing papers by Pei Ye

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 50 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201658
2 202148
3 201948
4 200138
5 201832
6 201926
7
Efficient Modeling of Excitable Cells Using Hybrid Automata
200525
8
NOD1, RIP2 and Caspase12 are potentially novel biomarkers for oral squamous cell carcinoma development and progression.
201424
9 202123
10 201823
11 201920
12 201820
13 201819
14 201516
15 202316
16 202115
17 201514
18 202410
19 201610
20 202410

About Pei Ye

Pei Ye is a scholar working on Molecular Biology, Immunology, Cancer Research, Biomedical Engineering and Computer Vision and Pattern Recognition, having authored 50 papers that have together received 601 indexed citations. Recurring topics across this work include Immune Response and Inflammation (6 papers), Industrial Vision Systems and Defect Detection (3 papers), Monoclonal and Polyclonal Antibodies Research (3 papers), MicroRNA in disease regulation (3 papers), Receptor Mechanisms and Signaling (2 papers), Circular RNAs in diseases (2 papers), NF-κB Signaling Pathways (2 papers) and Optical measurement and interference techniques (2 papers). The work is most often cited by research in Applied Psychology (45 citations), Periodontics (36 citations), Immunology (93 citations), Cancer Research (64 citations) and Molecular Biology (218 citations). Pei Ye has collaborated with scholars based in China, United States and United Kingdom. Frequent co-authors include Xiang Wang, Xue Li, Junhui Kong, Ting Zhou, Radu Grosu, Wenmei Wang, Xiaodong Han, Emilia Entcheva, Ning Duan and José A. López. Their work appears in journals such as Journal of Biological Chemistry, Biomedicine & Pharmacotherapy, Toxicology and Industrial Health, Frontiers in Immunology and BMC Veterinary Research.

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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