Gregory Dyson
Impact in
- Cancer Research top 5%
- MicroRNA in disease regulation
- Cancer-related molecular mechanisms research
- Cancer, Lipids, and Metabolism
- Oncology top 10%
Papers in
-
- Cancer Genomics and Diagnostics 10
- Cancer, Lipids, and Metabolism 7
- Cancer-related molecular mechanisms research 7
- Co-authors
- Fazlul H. Sarkar (4 shared papers)Dejuan Kong (2 shared papers)Krishna Rao Maddipati (2 shared papers)Paul J. Williams (1 shared paper)Xuebao Zhang (1 shared paper)Stephen A. Duncan (1 shared paper)Chunbin Zhang (1 shared paper)Guohui Wang (1 shared paper)
- Journals
- Journal of Clinical Oncology (7 papers)Blood (6 papers)PLoS ONE (4 papers)Oncotarget (3 papers)Scientific Reports (2 papers)
- Partner nations
- United StatesSouth KoreaQatar
In The Last Decade
Gregory Dyson
68 papers receiving 1.1k citations
Peers
Comparison fields: 5 of 98
- Cancer Research 326
- Oncology 304
- Molecular Biology 577
- Biochemistry 46
- Cell Biology 98
Countries citing papers authored by Gregory Dyson
This map shows the geographic impact of Gregory Dyson'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 Gregory Dyson with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Gregory Dyson more than expected).
Fields of papers citing papers by Gregory Dyson
This network shows the impact of papers produced by Gregory Dyson. 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 Gregory Dyson. The network helps show where Gregory Dyson may publish in the future.
Co-authors
The 25 scholars most cited alongside Gregory Dyson, 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 74 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2011 | 161 | |
| 2 | 2012 | 86 | |
| 3 | 2017 | 42 | |
| 4 | 2020 | 42 | |
| 5 | 2019 | 40 | |
| 6 | Comprehensive molecular oncogenomic profiling and miRNA analysis of prostate cancer. | 2013 | 39 |
| 7 | 2014 | 38 | |
| 8 | 2014 | 35 | |
| 9 | 2016 | 34 | |
| 10 | 2017 | 34 | |
| 11 | 2011 | 30 | |
| 12 | 2015 | 29 | |
| 13 | 2016 | 29 | |
| 14 | 2018 | 25 | |
| 15 | 2019 | 24 | |
| 16 | 2017 | 24 | |
| 17 | 2021 | 24 | |
| 18 | 2017 | 23 | |
| 19 | 2022 | 21 | |
| 20 | 2020 | 19 |
About Gregory Dyson
Gregory Dyson is a scholar working on Cancer Research, Molecular Biology, Oncology, Pulmonary and Respiratory Medicine and Hematology, having authored 74 papers that have together received 1.1k indexed citations. Recurring topics across this work include Cancer Genomics and Diagnostics (10 papers), Cancer, Lipids, and Metabolism (7 papers), Acute Myeloid Leukemia Research (7 papers), Cancer-related molecular mechanisms research (7 papers), Pancreatic and Hepatic Oncology Research (7 papers), Lung Cancer Research Studies (6 papers), BRCA gene mutations in cancer (4 papers) and Immune Cell Function and Interaction (4 papers). The work is most often cited by research in Cancer Research (326 citations), Oncology (304 citations), Molecular Biology (577 citations), Biochemistry (46 citations) and Cell Biology (98 citations). Gregory Dyson has collaborated with scholars based in United States, South Korea and Qatar. Frequent co-authors include Fazlul H. Sarkar, Dejuan Kong, Krishna Rao Maddipati, Paul J. Williams, Xuebao Zhang, Stephen A. Duncan, Chunbin Zhang, Guohui Wang, Randal J. Kaufman and Ze Zheng. Their work appears in journals such as Journal of Clinical Oncology, Blood, PLoS ONE, Oncotarget and Scientific Reports.
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.