Yi‐Mi Wu
Impact in
- Cancer Research top 1%
- MicroRNA in disease regulation
- Cancer-related molecular mechanisms research
- Molecular Biology top 5%
- Circular RNAs in diseases
- RNA modifications and cancer
- RNA Research and Splicing
- PI3K/AKT/mTOR signaling in cancer
Papers in
-
- Acute Myeloid Leukemia Research 4
- Chronic Myeloid Leukemia Treatments 4
- Multiple Myeloma Research and Treatments 3
-
- Cancer Genomics and Diagnostics 10
- Co-authors
- Dan R. RobinsonSu‐Fang LinArul M. ChinnaiyanXuhong CaoMarcin CieślikLanbo XiaoAlexey I. NesvizhskiiSudhanshu Shukla
- Journals
- JCO Precision Oncology (6 papers)Journal of Clinical Oncology (6 papers)Cancer Research (4 papers)Blood (3 papers)Clinical Cancer Research (2 papers)
- Partner nations
- United StatesTaiwanAustralia
In The Last Decade
Yi‐Mi Wu
43 papers receiving 2.4k citations
Hit Papers
Peers
Comparison fields: 5 of 106
- Cancer Research 1.2k
- Molecular Biology 1.9k
- Oncology 361
- Hematology 112
- Immunology 209
Countries citing papers authored by Yi‐Mi Wu
This map shows the geographic impact of Yi‐Mi 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 Yi‐Mi Wu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Yi‐Mi Wu more than expected).
Fields of papers citing papers by Yi‐Mi Wu
This network shows the impact of papers produced by Yi‐Mi 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 Yi‐Mi Wu. The network helps show where Yi‐Mi Wu may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Yi‐Mi 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
| # | Work | ||
|---|---|---|---|
| 1 | 2023 | 3 | |
| 2 | 2023 | 2 | |
| 3 | 2023 | 1 | |
| 4 | 2023 | 1 | |
| 5 | 2023 | 6 | |
| 6 | 2022 | 1 | |
| 7 | 2021 | 10 | |
| 8 | 2020 | 7 | |
| 9 | 2020 | 1 | |
| 10 | The Landscape of Circular RNA in Cancer Hit paper breakdown → | 2019 | 1188 |
| 11 | 2019 | 6 | |
| 12 | 2019 | 160 | |
| 13 | 2018 | 2 | |
| 14 | 2018 | 1 | |
| 15 | 2017 | 7 | |
| 16 | 2016 | 2 | |
| 17 | The protein tyrosine kinase family of the human genome Hit paper breakdown → | 2000 | 830 |
| 18 | 1997 | 72 | |
| 19 | 1996 | 10 | |
| 20 | 1996 | 31 |
About Yi‐Mi Wu
Yi‐Mi Wu is a scholar working on Hematology, Cancer Research, Genetics, Rheumatology and Pulmonary and Respiratory Medicine, having authored 44 papers that have together received 2.5k indexed citations. Recurring topics across this work include Cancer Genomics and Diagnostics (10 papers), Prostate Cancer Treatment and Research (6 papers), Myeloproliferative Neoplasms: Diagnosis and Treatment (5 papers), Acute Myeloid Leukemia Research (4 papers), Chronic Myeloid Leukemia Treatments (4 papers), Multiple Myeloma Research and Treatments (3 papers), Cholangiocarcinoma and Gallbladder Cancer Studies (3 papers) and Neuroscience and Neuropharmacology Research (3 papers). The work is most often cited by research in Cancer Research (1.2k citations), Molecular Biology (1.9k citations), Oncology (361 citations), Hematology (112 citations) and Immunology (209 citations). Yi‐Mi Wu has collaborated with scholars based in United States, Taiwan and Australia. Frequent co-authors include Dan R. Robinson, Su‐Fang Lin, Arul M. Chinnaiyan, Xuhong Cao, Marcin Cieślik, Lanbo Xiao, Alexey I. Nesvizhskii, Sudhanshu Shukla, Yajia Zhang and Yuping Zhang. Their work appears in journals such as JCO Precision Oncology, Journal of Clinical Oncology, Cancer Research, Blood and Clinical Cancer Research.
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.