Haiyun Cheng
Impact in
- Oncology top 5%
- Cancer Cells and Metastasis
- Cytokine Signaling Pathways and Interactions
- Cancer Research top 10%
- Cancer-related molecular mechanisms research
- MicroRNA in disease regulation
Papers in
-
- Ubiquitin and proteasome pathways 1
- Oncology 5
- Cytokine Signaling Pathways and Interactions 4
- Co-authors
- Thomas E. Smithgall (6 shared papers)Paulo M. Hoff (1 shared paper)Anthony D. Yang (1 shared paper)Michael J. Gray (1 shared paper)George Van Buren (1 shared paper)Wenbiao Liu (1 shared paper)Lee M. Ellis (1 shared paper)Ray Somcio (1 shared paper)
- Journals
- Molecular and Cellular Biology (3 papers)Oncogene (2 papers)British Journal of Haematology (1 paper)Clinical Cancer Research (1 paper)NMR in Biomedicine (1 paper)
- Partner nations
- United StatesChina
In The Last Decade
Haiyun Cheng
12 papers receiving 962 citations
Peers
Comparison fields: 5 of 78
- Oncology 443
- Cancer Research 172
- Molecular Biology 534
- Hematology 72
- Cell Biology 95
Countries citing papers authored by Haiyun Cheng
This map shows the geographic impact of Haiyun Cheng'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 Haiyun Cheng with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Haiyun Cheng more than expected).
Fields of papers citing papers by Haiyun Cheng
This network shows the impact of papers produced by Haiyun Cheng. 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 Haiyun Cheng. The network helps show where Haiyun Cheng may publish in the future.
Co-authors
The 25 scholars most cited alongside Haiyun Cheng, 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 | 2006 | 452 | |
| 2 | 2000 | 119 | |
| 3 | Identification and characterization of signal transducer and activator of transcription 3 recruitment sites within the epidermal growth factor receptor. | 2003 | 115 |
| 4 | 2004 | 60 | |
| 5 | 1998 | 54 | |
| 6 | 2004 | 54 | |
| 7 | 2007 | 43 | |
| 8 | 2001 | 35 | |
| 9 | 1999 | 31 | |
| 10 | 2015 | 5 | |
| 11 | 2015 | 3 | |
| 12 | 2023 | 1 |
About Haiyun Cheng
Haiyun Cheng is a scholar working on Molecular Biology, Oncology, Hematology, Genetics and Pathology and Forensic Medicine, having authored 12 papers that have together received 972 indexed citations. Recurring topics across this work include Cytokine Signaling Pathways and Interactions (4 papers), Cancer Mechanisms and Therapy (2 papers), Chronic Myeloid Leukemia Treatments (2 papers), Acute Myeloid Leukemia Research (2 papers), NF-κB Signaling Pathways (1 paper), Ubiquitin and proteasome pathways (1 paper), Mycobacterium research and diagnosis (1 paper) and Species Distribution and Climate Change (1 paper). The work is most often cited by research in Oncology (443 citations), Cancer Research (172 citations), Molecular Biology (534 citations), Hematology (72 citations) and Cell Biology (95 citations). Haiyun Cheng has collaborated with scholars based in United States and China. Frequent co-authors include Thomas E. Smithgall, Paulo M. Hoff, Anthony D. Yang, Michael J. Gray, George Van Buren, Wenbiao Liu, Lee M. Ellis, Ray Somcio, E. Ramsay Camp and David J. Tweardy. Their work appears in journals such as Molecular and Cellular Biology, Oncogene, British Journal of Haematology, Clinical Cancer Research and NMR in Biomedicine.
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.