Matthew S. Waitkus
Impact in
- Genetics top 2%
- Glioma Diagnosis and Treatment
- Cancer Research top 10%
- Cancer, Hypoxia, and Metabolism
- MicroRNA in disease regulation
- Cancer Genomics and Diagnostics
Papers in
-
- DNA Repair Mechanisms 3
- Epigenetics and DNA Methylation 3
- Histone Deacetylase Inhibitors Research 3
- Cell death mechanisms and regulation 2
- Genetics 9
- Glioma Diagnosis and Treatment 9
- Co-authors
- Hai Yan (12 shared papers)Bill H. Diplas (12 shared papers)Paul E. DiCorleto (5 shared papers)Roger E. McLendon (6 shared papers)Christopher J. Pirozzi (9 shared papers)Landon J. Hansen (5 shared papers)Yiping He (6 shared papers)Unni M. Chandrasekharan (4 shared papers)
- Journals
- Neuro-Oncology (5 papers)Cancer Research (3 papers)Molecular Cancer Research (3 papers)Arteriosclerosis Thrombosis and Vascular Biology (2 papers)iScience (1 paper)
- Partner nations
- United StatesChinaPakistan
In The Last Decade
Matthew S. Waitkus
24 papers receiving 802 citations
Peers
Comparison fields: 5 of 73
- Genetics 313
- Cancer Research 248
- Molecular Biology 392
- Hematology 53
- Oncology 120
Countries citing papers authored by Matthew S. Waitkus
This map shows the geographic impact of Matthew S. Waitkus'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 Matthew S. Waitkus with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Matthew S. Waitkus more than expected).
Fields of papers citing papers by Matthew S. Waitkus
This network shows the impact of papers produced by Matthew S. Waitkus. 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 Matthew S. Waitkus. The network helps show where Matthew S. Waitkus may publish in the future.
Co-authors
The 25 scholars most cited alongside Matthew S. Waitkus, 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 25 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2018 | 231 | |
| 2 | 2015 | 216 | |
| 3 | 2014 | 37 | |
| 4 | 2024 | 36 | |
| 5 | 2018 | 36 | |
| 6 | 2017 | 34 | |
| 7 | 2017 | 33 | |
| 8 | 2017 | 31 | |
| 9 | 2020 | 20 | |
| 10 | 2019 | 19 | |
| 11 | 2019 | 18 | |
| 12 | 2020 | 14 | |
| 13 | 2023 | 12 | |
| 14 | 2010 | 12 | |
| 15 | 2021 | 12 | |
| 16 | 2014 | 11 | |
| 17 | 2024 | 10 | |
| 18 | 2013 | 9 | |
| 19 | 2013 | 5 | |
| 20 | 2023 | 3 |
About Matthew S. Waitkus
Matthew S. Waitkus is a scholar working on Molecular Biology, Genetics, Cancer Research, Oncology and Physiology, having authored 25 papers that have together received 804 indexed citations. Recurring topics across this work include Glioma Diagnosis and Treatment (9 papers), Telomeres, Telomerase, and Senescence (4 papers), Cancer, Hypoxia, and Metabolism (4 papers), DNA Repair Mechanisms (3 papers), Epigenetics and DNA Methylation (3 papers), Histone Deacetylase Inhibitors Research (3 papers), Cell death mechanisms and regulation (2 papers) and MicroRNA in disease regulation (2 papers). The work is most often cited by research in Genetics (313 citations), Cancer Research (248 citations), Molecular Biology (392 citations), Hematology (53 citations) and Oncology (120 citations). Matthew S. Waitkus has collaborated with scholars based in United States, China and Pakistan. Frequent co-authors include Hai Yan, Bill H. Diplas, Paul E. DiCorleto, Roger E. McLendon, Christopher J. Pirozzi, Landon J. Hansen, Yiping He, Unni M. Chandrasekharan, Darell D. Bigner and Rui Yang. Their work appears in journals such as Neuro-Oncology, Cancer Research, Molecular Cancer Research, Arteriosclerosis Thrombosis and Vascular Biology and iScience.
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.