Mingjun Yang

1.4k citations
41 papers · 1.0k · h-index 20

Impact in

Papers in

    • Protein Structure and Dynamics 18
    • Glycosylation and Glycoproteins Research 4
    • RNA and protein synthesis mechanisms 3
    • Enzyme Structure and Function 6
    • Machine Learning in Materials Science 5

Mingjun Yang

39 papers receiving 995 citations

Peers

Mingjun Yang
Comparison fields: 5 of 113
  • Biomaterials 188
  • Computational Theory and Mathematics 154
  • Physical and Theoretical Chemistry 86
  • Endocrinology 35
  • Molecular Biology 444
Replace Nathan R. Kern with:
Nathan R. Kern United States
Roland G. Huber Singapore
Noriyuki Igarashi Japan
Franci Merzel Slovenia
Sumati Bhatia Germany
Pnina Dauber‐Osguthorpe United Kingdom
Mary T. McBride United States
Nicholas C. Fitzkee United States
María Grazia Ortore Italy
M. Genest France
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Citations per field
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Citations per year

Countries citing papers authored by Mingjun Yang

Since Specialization
Citations

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

Fields of papers citing papers by Mingjun Yang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 41 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2008119
2 201096
3 201561
4 202058
5 201849
6 202346
7 201046
8 201740
9 201538
10 201535
11 201733
12 202033
13 201432
14 201829
15 200929
16 202127
17 201627
18 201427
19 202023
20 201922

About Mingjun Yang

Mingjun Yang is a scholar working on Molecular Biology, Materials Chemistry, Computational Theory and Mathematics, Atomic and Molecular Physics, and Optics and Spectroscopy, having authored 41 papers that have together received 1.0k indexed citations. Recurring topics across this work include Protein Structure and Dynamics (18 papers), Computational Drug Discovery Methods (8 papers), Enzyme Structure and Function (6 papers), Machine Learning in Materials Science (5 papers), Glycosylation and Glycoproteins Research (4 papers), Spectroscopy and Quantum Chemical Studies (4 papers), Crystallography and molecular interactions (3 papers) and RNA and protein synthesis mechanisms (3 papers). The work is most often cited by research in Biomaterials (188 citations), Computational Theory and Mathematics (154 citations), Physical and Theoretical Chemistry (86 citations), Endocrinology (35 citations) and Molecular Biology (444 citations). Mingjun Yang has collaborated with scholars based in United States, China and Denmark. Frequent co-authors include Alexander D. MacKerell, S. L. S. Stipp, John H. Harding, Keli Han, Kenno Vanommeslaeghe, Jing Huang, Asaminew H. Aytenfisu, Xin Zhang, Tue Hassenkam and K. Bechgaard. Their work appears in journals such as Crystal Growth & Design, Journal of Chemical Information and Modeling, Journal of Chemical Theory and Computation, The Journal of Chemical Physics and Advances in experimental medicine and biology.

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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