Chia‐en A. Chang
- Molecular Biology top 5%
- Materials Chemistry top 10%
- Computational Theory and Mathematics top 0.5%
- Organic Chemistry top 5%
- Spectroscopy top 5%
- Co-authors
- Michael K. GilsonWei ChenJ. Andrew McCammonValentina TozziniJoanna TrylskaZhiye TangWanli YouChristopher Roberts
- Topics
- Protein Structure and Dynamics (36 papers)Enzyme Structure and Function (18 papers)Computational Drug Discovery Methods (18 papers)
- Journals
- Proceedings of the National Academy of SciencesJournal of the American Chemical SocietyNucleic Acids Research
- Partner nations
- United StatesChinaItaly
In The Last Decade
Chia‐en A. Chang
86 papers receiving 2.9k citations
Peers
Comparison fields: 5 of 130
- Molecular Biology 2.1k
- Materials Chemistry 676
- Computational Theory and Mathematics 612
- Organic Chemistry 418
- Spectroscopy 304
Countries citing papers authored by Chia‐en A. Chang
This map shows the geographic impact of Chia‐en A. 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 Chia‐en A. Chang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Chia‐en A. Chang more than expected).
Fields of papers citing papers by Chia‐en A. Chang
This network shows the impact of papers produced by Chia‐en A. 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 Chia‐en A. Chang. The network helps show where Chia‐en A. Chang may publish in the future.
Co-authorship network of co-authors of Chia‐en A. Chang
This figure shows the co-authorship network connecting the top 25 collaborators of Chia‐en A. Chang. A scholar is included among the top collaborators of Chia‐en A. Chang 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 Chia‐en A. Chang. Chia‐en A. Chang is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 4 | |
| 2 | 8 | |
| 3 | 5 | |
| 4 | 3 | |
| 5 | 6 | |
| 6 | 43 | |
| 7 | 4 | |
| 8 | 3 | |
| 9 | 7 | |
| 10 | 13 | |
| 11 | 21 | |
| 12 | 4 | |
| 13 | 11 | |
| 14 | 83 | |
| 15 | 66 | |
| 16 | 55 | |
| 17 | 95 | |
| 18 | 69 | |
| 19 | 207 | |
| 20 | 103 |
About Chia‐en A. Chang
Chia‐en A. Chang is a scholar working on Virology, Computational Theory and Mathematics and Molecular Biology, having authored 87 papers that have together received 3.0k indexed citations. Recurring topics across this work include Protein Structure and Dynamics (36 papers), Enzyme Structure and Function (18 papers) and Computational Drug Discovery Methods (18 papers). The work is most often cited by research in Computational Theory and Mathematics (612 citations), Virology (155 citations) and Molecular Biology (2.1k citations). Chia‐en A. Chang has collaborated with scholars based in United States, China and Italy. Frequent co-authors include Michael K. Gilson, Wei Chen, J. Andrew McCammon, Valentina Tozzini, Joanna Trylska, Zhiye Tang, Wei Chen, Wanli You, Wei Chen and Christopher Roberts. Their work appears in journals such as Proceedings of the National Academy of Sciences, Journal of the American Chemical Society and Nucleic Acids Research.
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.