William W. Chin
- Reproductive Medicine top 1%
- Genetics top 5%
- Endocrinology, Diabetes and Metabolism top 2%
- Molecular Biology
- Public Health, Environmental and Occupational Health top 5%
- Co-authors
- Margaret A. ShupnikSoheyla GharibMargaret E. WiermanE. Chester RidgwayMichael S. GordonRona S. CarrollAnne CorriganWylie Vale
- Topics
- Growth Hormone and Insulin-like Growth Factors (13 papers)Thyroid Disorders and Treatments (8 papers)Estrogen and related hormone effects (7 papers)
- Journals
- Endocrine ReviewsEndocrinologyGene
- Partner nations
- United StatesSwitzerlandCanada
In The Last Decade
William W. Chin
18 papers receiving 1.5k citations
Hit Papers
Peers
Comparison fields: 5 of 76
- Reproductive Medicine 685
- Genetics 681
- Endocrinology, Diabetes and Metabolism 636
- Molecular Biology 488
- Public Health, Environmental and Occupational Health 281
Countries citing papers authored by William W. Chin
This map shows the geographic impact of William W. Chin'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 William W. Chin with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites William W. Chin more than expected).
Fields of papers citing papers by William W. Chin
This network shows the impact of papers produced by William W. Chin. 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 William W. Chin. The network helps show where William W. Chin may publish in the future.
Co-authorship network of co-authors of William W. Chin
This figure shows the co-authorship network connecting the top 25 collaborators of William W. Chin. A scholar is included among the top collaborators of William W. Chin 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 William W. Chin. William W. Chin is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 64 | |
| 2 | 36 | |
| 3 | 22 | |
| 4 | 8 | |
| 5 | 40 | |
| 6 | 63 | |
| 7 | 46 | |
| 8 | 5 | |
| 9 | Molecular Biology of the Pituitary Gonadotropinsbreakdown → | 565 |
| 10 | 201 | |
| 11 | 107 | |
| 12 | 164 | |
| 13 | 45 | |
| 14 | 35 | |
| 15 | 7 | |
| 16 | 88 | |
| 17 | 9 | |
| 18 | 29 |
About William W. Chin
William W. Chin is a scholar working on Endocrinology, Diabetes and Metabolism, Reproductive Medicine and Behavioral Neuroscience, having authored 18 papers that have together received 1.5k indexed citations. Recurring topics across this work include Growth Hormone and Insulin-like Growth Factors (13 papers), Thyroid Disorders and Treatments (8 papers) and Estrogen and related hormone effects (7 papers). The work is most often cited by research in Reproductive Medicine (685 citations), Endocrinology, Diabetes and Metabolism (636 citations) and Genetics (681 citations). William W. Chin has collaborated with scholars based in United States, Switzerland and Canada. Frequent co-authors include Margaret A. Shupnik, Soheyla Gharib, Margaret E. Wierman, E. Chester Ridgway, Michael S. Gordon, Rona S. Carroll, Anne Corrigan, Wylie Vale, Douglas S. Ross and Douglas S. Darling. Their work appears in journals such as Endocrine Reviews, Endocrinology and Gene.
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.