Donald Jin
Impact in
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- Monoclonal and Polyclonal Antibodies Research
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- TGF-β signaling in diseases
- Glycosylation and Glycoproteins Research
- Protein purification and stability
Papers in
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- TGF-β signaling in diseases 3
- Receptor Mechanisms and Signaling 2
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- Neuropeptides and Animal Physiology 2
- Co-authors
- Charles A. West (2 shared papers)William C. Okulicz (2 shared papers)Hermann Oppermann (3 shared papers)Karl Muffly (2 shared papers)James S. Huston (2 shared papers)John E. McCartney (2 shared papers)Mei-Sheng Tai (2 shared papers)Peter Keck (1 shared paper)
- Journals
- PLANT PHYSIOLOGY (2 papers)Molecular Endocrinology (2 papers)Protein Engineering Design and Selection (1 paper)Endocrinology (1 paper)International Reviews of Immunology (1 paper)
- Partner nations
- United StatesFranceSweden
In The Last Decade
Donald Jin
11 papers receiving 621 citations
Peers
Comparison fields: 5 of 77
- Radiology, Nuclear Medicine and Imaging 156
- Molecular Biology 385
- Reproductive Medicine 45
- Cellular and Molecular Neuroscience 89
- Plant Science 173
Countries citing papers authored by Donald Jin
This map shows the geographic impact of Donald Jin'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 Donald Jin with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Donald Jin more than expected).
Fields of papers citing papers by Donald Jin
This network shows the impact of papers produced by Donald Jin. 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 Donald Jin. The network helps show where Donald Jin may publish in the future.
Co-authors
The 25 scholars most cited alongside Donald Jin, 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 | 1993 | 138 | |
| 2 | 1984 | 127 | |
| 3 | Expression of bone morphogenetic protein receptors type-IA, -IB and -II correlates with tumor grade in human prostate cancer tissues. | 2000 | 83 |
| 4 | 1984 | 61 | |
| 5 | 1988 | 60 | |
| 6 | 1995 | 42 | |
| 7 | 2000 | 41 | |
| 8 | 1989 | 35 | |
| 9 | 1988 | 35 | |
| 10 | 1997 | 20 | |
| 11 | 1999 | 13 |
About Donald Jin
Donald Jin is a scholar working on Molecular Biology, Cellular and Molecular Neuroscience, Oncology, Rheumatology and Radiology, Nuclear Medicine and Imaging, having authored 11 papers that have together received 655 indexed citations. Recurring topics across this work include TGF-β signaling in diseases (3 papers), Neuropeptides and Animal Physiology (2 papers), Monoclonal and Polyclonal Antibodies Research (2 papers), Receptor Mechanisms and Signaling (2 papers), Neuroendocrine regulation and behavior (1 paper), Peptidase Inhibition and Analysis (1 paper), Radiopharmaceutical Chemistry and Applications (1 paper) and Polysaccharides and Plant Cell Walls (1 paper). The work is most often cited by research in Radiology, Nuclear Medicine and Imaging (156 citations), Molecular Biology (385 citations), Reproductive Medicine (45 citations), Cellular and Molecular Neuroscience (89 citations) and Plant Science (173 citations). Donald Jin has collaborated with scholars based in United States, France and Sweden. Frequent co-authors include Charles A. West, William C. Okulicz, Hermann Oppermann, Karl Muffly, James S. Huston, John E. McCartney, Mei-Sheng Tai, Peter Keck, Daniel L. Kilpatrick and Michel M. Sanders. Their work appears in journals such as PLANT PHYSIOLOGY, Molecular Endocrinology, Protein Engineering Design and Selection, Endocrinology and International Reviews of Immunology.
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.