Lei Pi

577 citations
48 papers · 427 · h-index 11

Impact in

    • Cancer-related molecular mechanisms research
    • MicroRNA in disease regulation
    • Kawasaki Disease and Coronary Complications

Papers in

Lei Pi

45 papers receiving 419 citations

Peers

Lei Pi
Comparison fields: 5 of 70
  • Cancer Research 93
  • Surgery 139
  • Immunology 69
  • Pulmonary and Respiratory Medicine 91
  • Molecular Biology 150
Replace Dianne Hillyard with:
Dianne Hillyard United Kingdom
Chuan Hu China
Chihao Zhang China
Stefano Scabini Italy
Farahnaz Waissi Netherlands
Andriy O. Samokhin United States
Tomonori Iida Japan
Manabu Tatokoro Japan
Lei Pi relative to Dianne Hillyard United Kingdom Dianne Hillyard's profile →
Citations per field
00.5×5.3×
Dianne Hillyard · 1×
Citations per year

Countries citing papers authored by Lei Pi

Since Specialization
Citations

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

Fields of papers citing papers by Lei Pi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 48 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201999
2 201931
3 201128
4 201927
5 201917
6 200914
7 201913
8 201811
9 201911
10 201811
11 201811
12 201810
13 201810
14 20189
15 20189
16
Modeling Uncertain and Imprecise Information in Process Modeling with UML.
20088
17 20228
18 20218
19 20218
20 20197

About Lei Pi

Lei Pi is a scholar working on Surgery, Pulmonary and Respiratory Medicine, Molecular Biology, Immunology and Cancer Research, having authored 48 papers that have together received 427 indexed citations. Recurring topics across this work include Kawasaki Disease and Coronary Complications (26 papers), Coronary Artery Anomalies (11 papers), Cancer-related molecular mechanisms research (7 papers), Reproductive System and Pregnancy (6 papers), Cardiovascular Issues in Pregnancy (5 papers), Inflammasome and immune disorders (5 papers), Autoimmune and Inflammatory Disorders Research (4 papers) and Circular RNAs in diseases (3 papers). The work is most often cited by research in Cancer Research (93 citations), Surgery (139 citations), Immunology (69 citations), Pulmonary and Respiratory Medicine (91 citations) and Molecular Biology (150 citations). Lei Pi has collaborated with scholars based in China, United States and France. Frequent co-authors include Xiaoqiong Gu, Di Che, Yufen Xu, Li Zhang, Ping Huang, Yaqian Tan, Zhaoliang Lu, Zhi Zeng, Renjing Liu and Wai Ho Tang. Their work appears in journals such as Frontiers in Genetics, Journal of Inflammation Research, Journal of Clinical Laboratory Analysis, Bioscience Reports and The Journal of Gene Medicine.

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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