May Chang
Impact in
-
- Neuropeptides and Animal Physiology
- Neurobiology and Insect Physiology Research
- Insect Science top 10%
Papers in
-
- Protein Hydrolysis and Bioactive Peptides 2
- Receptor Mechanisms and Signaling 2
-
- Neuropeptides and Animal Physiology 6
- Co-authors
- John Eng (6 shared papers)Rosalyn S. Yalow (6 shared papers)Masato Koreeda (2 shared papers)Kazuki Nakanishi (2 shared papers)Yu‐Ching E. Pan (4 shared papers)Hui-Ju Hsu (1 shared paper)Shizuka Sasaki (1 shared paper)Y C Pan (4 shared papers)
- Journals
- Library Hi Tech (2 papers)Peptides (2 papers)Archives of Biochemistry and Biophysics (2 papers)Life Sciences (2 papers)Tetrahedron Letters (1 paper)
- Partner nations
- United StatesSwitzerlandItaly
In The Last Decade
May Chang
17 papers receiving 515 citations
Peers
Comparison fields: 5 of 92
- Cellular and Molecular Neuroscience 281
- Insect Science 58
- Molecular Biology 282
- Reproductive Medicine 31
- Endocrine and Autonomic Systems 23
Countries citing papers authored by May Chang
This map shows the geographic impact of May 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 May Chang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites May Chang more than expected).
Fields of papers citing papers by May Chang
This network shows the impact of papers produced by May 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 May Chang. The network helps show where May Chang may publish in the future.
Co-authors
The 25 scholars most cited alongside May Chang, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 1966 | 114 | |
| 2 | 1985 | 81 | |
| 3 | 1986 | 79 | |
| 4 | 1984 | 64 | |
| 5 | 1985 | 46 | |
| 6 | 1984 | 37 | |
| 7 | 1968 | 26 | |
| 8 | 1986 | 25 | |
| 9 | 1986 | 23 | |
| 10 | 1985 | 19 | |
| 11 | 2010 | 12 | |
| 12 | 1985 | 12 | |
| 13 | 1985 | 11 | |
| 14 | 2006 | 10 | |
| 15 | 2000 | 7 | |
| 16 | 2018 | 2 | |
| 17 | 1984 | 1 |
About May Chang
May Chang is a scholar working on Molecular Biology, Cellular and Molecular Neuroscience, Oncology, Surgery and Information Systems, having authored 17 papers that have together received 569 indexed citations. Recurring topics across this work include Neuropeptides and Animal Physiology (6 papers), Peptidase Inhibition and Analysis (3 papers), Protein Hydrolysis and Bioactive Peptides (2 papers), Receptor Mechanisms and Signaling (2 papers), Mass Spectrometry Techniques and Applications (2 papers), Open Source Software Innovations (1 paper), Advanced Proteomics Techniques and Applications (1 paper) and Insect Pheromone Research and Control (1 paper). The work is most often cited by research in Cellular and Molecular Neuroscience (281 citations), Insect Science (58 citations), Molecular Biology (282 citations), Reproductive Medicine (31 citations) and Endocrine and Autonomic Systems (23 citations). May Chang has collaborated with scholars based in United States, Switzerland and Italy. Frequent co-authors include John Eng, Rosalyn S. Yalow, Masato Koreeda, Kazuki Nakanishi, Yu‐Ching E. Pan, Hui-Ju Hsu, Shizuka Sasaki, Y C Pan, J D Hulmes and Jeffrey D. Hulmes. Their work appears in journals such as Library Hi Tech, Peptides, Archives of Biochemistry and Biophysics, Life Sciences and Tetrahedron Letters.
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.