Junhan Chang

894 citations
5 papers · 107 · h-index 4

Impact in

Papers in

    • Protein Structure and Dynamics 4
    • RNA and protein synthesis mechanisms 1
    • Machine Learning in Materials Science 3
    • Enzyme Structure and Function 1

Junhan Chang

5 papers receiving 106 citations

Peers

Junhan Chang
Comparison fields: 5 of 41
  • Computational Theory and Mathematics 28
  • Materials Chemistry 75
  • Statistical and Nonlinear Physics 12
  • Structural Biology 1
  • Molecular Biology 46
Replace Hannah M. Baumann with:
Hannah M. Baumann United States
Dedi Wang United States
Jigyasa Nigam Switzerland
Yundian Zeng China
Dominik Lemm Germany
Raúl P. Peláez Spain
Levi N. Naden United States
Haixin Wei United States
Arif Ullah China
Niklas W. A. Gebauer Germany
Junhan Chang relative to Hannah M. Baumann United States Hannah M. Baumann's profile →
Citations per field
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Hannah M. Baumann · 1×
Citations per year

Countries citing papers authored by Junhan Chang

Since Specialization
Citations

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

Fields of papers citing papers by Junhan Chang

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

5 of 5 papers shown

About Junhan Chang

Junhan Chang is a scholar working on Molecular Biology, Materials Chemistry, Computational Theory and Mathematics, Atomic and Molecular Physics, and Optics and Cell Biology, having authored 5 papers that have together received 107 indexed citations. Recurring topics across this work include Protein Structure and Dynamics (4 papers), Machine Learning in Materials Science (3 papers), Computational Drug Discovery Methods (2 papers), Enzyme Structure and Function (1 paper), Mass Spectrometry Techniques and Applications (1 paper), Bacterial Genetics and Biotechnology (1 paper), Endoplasmic Reticulum Stress and Disease (1 paper) and RNA and protein synthesis mechanisms (1 paper). The work is most often cited by research in Computational Theory and Mathematics (28 citations), Materials Chemistry (75 citations), Statistical and Nonlinear Physics (12 citations), Structural Biology (1 citation) and Molecular Biology (46 citations). Junhan Chang has collaborated with scholars based in China, Germany and Ukraine. Frequent co-authors include Linfeng Zhang, Yi Yang, Lijiang Yang, Dongdong Wang, Yi Qin Gao, Maodong Li, Handong Wang, Yanze Wang, Jun Zhang and Zhen Zhang. Their work appears in journals such as Nature Computational Science, Nature Chemical Biology, Journal of Chemical Theory and Computation, The Journal of Physical Chemistry B and The Journal of Physical Chemistry A.

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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