Yu‐Ling Wu
Impact in
- Cancer Research top 10%
- Protease and Inhibitor Mechanisms
- MicroRNA in disease regulation
- Cell Biology top 10%
- Endoplasmic Reticulum Stress and Disease
Papers in
-
- Mitochondrial Function and Pathology 6
- Muscle Physiology and Disorders 3
- Natural product bioactivities and synthesis 2
-
- Genetic Neurodegenerative Diseases 7
- Co-authors
- Linda M. Boxer (2 shared papers)David H. Perlmutter (1 shared paper)Paul J. Hippenmeyer (1 shared paper)Kirsty Moore (1 shared paper)Ernesto P. Molmenti (1 shared paper)Caroline A. Heckman (1 shared paper)Magdalena Arcinas (1 shared paper)Xu‐Rong Jiang (5 shared papers)
- Journals
- Scientific Reports (3 papers)British Journal of Haematology (2 papers)Leukemia Research (2 papers)Free Radical Biology and Medicine (2 papers)Antioxidants (2 papers)
- Partner nations
- TaiwanChinaUnited States
In The Last Decade
Yu‐Ling Wu
36 papers receiving 950 citations
Peers
Comparison fields: 5 of 89
- Cancer Research 189
- Cell Biology 131
- Molecular Biology 550
- Oncology 187
- Hematology 62
Countries citing papers authored by Yu‐Ling Wu
This map shows the geographic impact of Yu‐Ling Wu'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 Yu‐Ling Wu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yu‐Ling Wu more than expected).
Fields of papers citing papers by Yu‐Ling Wu
This network shows the impact of papers produced by Yu‐Ling Wu. 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 Yu‐Ling Wu. The network helps show where Yu‐Ling Wu may publish in the future.
Co-authors
The 25 scholars most cited alongside Yu‐Ling Wu, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 41 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 1994 | 221 | |
| 2 | 2001 | 180 | |
| 3 | 2021 | 61 | |
| 4 | 2010 | 56 | |
| 5 | 2006 | 55 | |
| 6 | 2017 | 48 | |
| 7 | 1998 | 39 | |
| 8 | 2010 | 38 | |
| 9 | 2017 | 28 | |
| 10 | 2000 | 28 | |
| 11 | 2015 | 21 | |
| 12 | 2017 | 20 | |
| 13 | 2002 | 19 | |
| 14 | 2020 | 13 | |
| 15 | 2021 | 13 | |
| 16 | 1996 | 13 | |
| 17 | 2000 | 12 | |
| 18 | 2022 | 10 | |
| 19 | 1995 | 10 | |
| 20 | 2019 | 10 |
About Yu‐Ling Wu
Yu‐Ling Wu is a scholar working on Molecular Biology, Cellular and Molecular Neuroscience, Immunology, Cancer Research and Oncology, having authored 41 papers that have together received 970 indexed citations. Recurring topics across this work include Genetic Neurodegenerative Diseases (7 papers), Mitochondrial Function and Pathology (6 papers), Acute Myeloid Leukemia Research (4 papers), Immune Cell Function and Interaction (3 papers), Immune Response and Inflammation (3 papers), Muscle Physiology and Disorders (3 papers), Cytokine Signaling Pathways and Interactions (2 papers) and Natural product bioactivities and synthesis (2 papers). The work is most often cited by research in Cancer Research (189 citations), Cell Biology (131 citations), Molecular Biology (550 citations), Oncology (187 citations) and Hematology (62 citations). Yu‐Ling Wu has collaborated with scholars based in Taiwan, China and United States. Frequent co-authors include Linda M. Boxer, David H. Perlmutter, Paul J. Hippenmeyer, Kirsty Moore, Ernesto P. Molmenti, Caroline A. Heckman, Magdalena Arcinas, Xu‐Rong Jiang, Adrian C. Newland and Stephen M. Kelsey. Their work appears in journals such as Scientific Reports, British Journal of Haematology, Leukemia Research, Free Radical Biology and Medicine and Antioxidants.
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.