Lin Hwang
Impact in
- Biological Psychiatry top 10%
- Tryptophan and brain disorders
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- Cancer Immunotherapy and Biomarkers
- Cancer Cells and Metastasis
Papers in
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- RNA Research and Splicing 2
- RNA and protein synthesis mechanisms 2
- RNA modifications and cancer 2
- TGF-β signaling in diseases 1
- Surgery 2
- Cholesterol and Lipid Metabolism 2
- Co-authors
- Kym F. Faull (11 shared papers)Sylvia Adams (1 shared paper)James Sayre (1 shared paper)Sara A. Hurvitz (1 shared paper)John A. Glaspy (1 shared paper)Dörthe Schaue (1 shared paper)Begoña Comı́n-Anduix (1 shared paper)Percy Lee (1 shared paper)
- Journals
- Journal of Lipid Research (2 papers)Clinical Cancer Research (1 paper)Journal of Huntington s Disease (1 paper)Journal of Biological Chemistry (1 paper)Psychoneuroendocrinology (1 paper)
- Partner nations
- United StatesFranceGermany
In The Last Decade
Lin Hwang
11 papers receiving 449 citations
Peers
Comparison fields: 5 of 80
- Biological Psychiatry 34
- Oncology 171
- Behavioral Neuroscience 22
- Immunology 102
- Cancer Research 55
Countries citing papers authored by Lin Hwang
This map shows the geographic impact of Lin Hwang'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 Lin Hwang with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Lin Hwang more than expected).
Fields of papers citing papers by Lin Hwang
This network shows the impact of papers produced by Lin Hwang. 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 Lin Hwang. The network helps show where Lin Hwang may publish in the future.
Co-authors
The 25 scholars most cited alongside Lin Hwang, 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 | 2018 | 205 | |
| 2 | 2019 | 43 | |
| 3 | 2015 | 41 | |
| 4 | 2016 | 39 | |
| 5 | 2017 | 29 | |
| 6 | 2015 | 23 | |
| 7 | 2016 | 21 | |
| 8 | 2016 | 18 | |
| 9 | 2015 | 17 | |
| 10 | 2016 | 11 | |
| 11 | 2017 | 5 |
About Lin Hwang
Lin Hwang is a scholar working on Molecular Biology, Surgery, Biochemistry, Cancer Research and Cellular and Molecular Neuroscience, having authored 11 papers that have together received 452 indexed citations. Recurring topics across this work include RNA Research and Splicing (2 papers), Cholesterol and Lipid Metabolism (2 papers), RNA and protein synthesis mechanisms (2 papers), RNA modifications and cancer (2 papers), Plant-Microbe Interactions and Immunity (1 paper), TGF-β signaling in diseases (1 paper), Biochemical Analysis and Sensing Techniques (1 paper) and Cancer, Lipids, and Metabolism (1 paper). The work is most often cited by research in Biological Psychiatry (34 citations), Oncology (171 citations), Behavioral Neuroscience (22 citations), Immunology (102 citations) and Cancer Research (55 citations). Lin Hwang has collaborated with scholars based in United States, France and Germany. Frequent co-authors include Kym F. Faull, Sylvia Adams, James Sayre, Sara A. Hurvitz, John A. Glaspy, Dörthe Schaue, Begoña Comı́n-Anduix, Percy Lee, Josephine A. Ratikan and Xiaochun Li. Their work appears in journals such as Journal of Lipid Research, Clinical Cancer Research, Journal of Huntington s Disease, Journal of Biological Chemistry and Psychoneuroendocrinology.
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.