Mingfei Wu

57 total papers · 439 total citations
33 papers, 272 citations indexed

About

Mingfei Wu is a scholar working on Molecular Biology, Oncology and Computer Vision and Pattern Recognition. According to data from OpenAlex, Mingfei Wu has authored 33 papers receiving a total of 272 indexed citations (citations by other indexed papers that have themselves been cited), including 15 papers in Molecular Biology, 10 papers in Oncology and 7 papers in Computer Vision and Pattern Recognition. Recurrent topics in Mingfei Wu's work include Protein Degradation and Inhibitors (12 papers), Ubiquitin and proteasome pathways (6 papers) and Multiple Myeloma Research and Treatments (4 papers). Mingfei Wu is often cited by papers focused on Protein Degradation and Inhibitors (12 papers), Ubiquitin and proteasome pathways (6 papers) and Multiple Myeloma Research and Treatments (4 papers). Mingfei Wu collaborates with scholars based in China, Macao and Czechia. Mingfei Wu's co-authors include Chen Li, Jinxin Che, Xiaowu Dong, Biao Yang, Zhengfa Liang, Wei Chen, Shenxin Zeng, Hao Li, Lixin Wei and Jianping Jiang and has published in prestigious journals such as Advanced Materials, International Journal of Molecular Sciences and Journal of Medicinal Chemistry.

In The Last Decade

Mingfei Wu

29 papers receiving 267 citations

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author						Papers	Cites
Mingfei Wu	88	54	49	27	26	33	272
Xiang Zhang	43 0.5×	13 0.2×	72 1.5×	19 0.7×	9 0.3×	54	323
Xubin Zheng	175 2.0×	10 0.2×	12 0.2×	4 0.1×	22 0.8×	21	287
Alexander Kim	28 0.3×	100 1.9×	20 0.4×	20 0.7×	21 0.8×	31	252
Meifeng Xu	92 1.0×	41 0.8×	22 0.4×	11 0.4×	9 0.3×	24	298
Shijie Zhou	56 0.6×	64 1.2×	28 0.6×	10 0.4×	57 2.2×	37	275
Huidan Wang	77 0.9×	21 0.4×	16 0.3×	10 0.4×	24 0.9×	17	294
Penglong Li	73 0.8×	78 1.4×	10 0.2×	20 0.7×	12 0.5×	20	267
Dominic Maggio	120 1.4×	45 0.8×	56 1.1×	2 0.1×	6 0.2×	23	326
Zixiong Wang	42 0.5×	37 0.7×	31 0.6×	10 0.4×	22 0.8×	27	268
Daniel Zhao	41 0.5×	4 0.1×	55 1.1×	6 0.2×	12 0.5×	30	267

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-authorship network of co-authors of Mingfei Wu

This figure shows the co-authorship network connecting the top 25 collaborators of Mingfei Wu. A scholar is included among the top collaborators of Mingfei Wu 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 Mingfei Wu. Mingfei Wu is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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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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