Mingfei Wu

462 citations
34 papers · 280 · h-index 10

Impact in

Papers in

    • Protein Degradation and Inhibitors 12
    • Ubiquitin and proteasome pathways 7
    • Peptidase Inhibition and Analysis 4

Mingfei Wu

31 papers receiving 276 citations

Peers

Mingfei Wu
Comparison fields: 5 of 95
  • Geology 24
  • Computer Vision and Pattern Recognition 54
  • Hematology 26
  • Environmental Engineering 27
  • Oncology 52
Replace Kyung-Ok Kim with:
Kyung-Ok Kim South Korea
Kyukwang Kim South Korea
Penglong Li China
Alexander Kim Russia
Periklis Papaioannou Greece
Alireza Khatamian United States
Jingcheng Chen China
Shijie Zhou China
Gongquan Li China
Han Bao China
Mingfei Wu relative to Kyung-Ok Kim South Korea Kyung-Ok Kim's profile →
Citations per field
00.5×5.2×
Kyung-Ok Kim · 1×
Citations per year

Countries citing papers authored by Mingfei Wu

Since Specialization
Citations

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

Fields of papers citing papers by Mingfei Wu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 34 papers — load more, or switch the sort, to bring in the rest.

#Work
1 202235
2 202231
3 202225
4 202421
5 201621
6 202118
7 202314
8 202311
9 202310
10 20249
11 20228
12 20248
13 20218
14 20216
15 20146
16 20216
17 20176
18 20245
19 20245
20 20225

About Mingfei Wu

Mingfei Wu is a scholar working on Molecular Biology, Oncology, Computer Vision and Pattern Recognition, Immunology and Geochemistry and Petrology, having authored 34 papers that have together received 280 indexed citations. Recurring topics across this work include Protein Degradation and Inhibitors (12 papers), Ubiquitin and proteasome pathways (7 papers), Advanced Vision and Imaging (4 papers), Multiple Myeloma Research and Treatments (4 papers), Geological Modeling and Analysis (4 papers), Peptidase Inhibition and Analysis (4 papers), 3D Surveying and Cultural Heritage (3 papers) and Invertebrate Immune Response Mechanisms (2 papers). The work is most often cited by research in Geology (24 citations), Computer Vision and Pattern Recognition (54 citations), Hematology (26 citations), Environmental Engineering (27 citations) and Oncology (52 citations). Mingfei Wu has collaborated with scholars based in China, Macao and Czechia. Frequent co-authors include Chen Li, Xiaowu Dong, Jinxin Che, Zhengfa Liang, Wei Chen, Biao Yang, Hao Li, Shenxin Zeng, Wenhai Huang and Lixin Wei. Their work appears in journals such as European Journal of Medicinal Chemistry, Journal of Medicinal Chemistry, Journal of Central South University, Environmental Science Nano and BMC Psychiatry.

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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