David Mysona
Impact in
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- Protease and Inhibitor Mechanisms
Papers in
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- Glycosylation and Glycoproteins Research 3
- Oncology 9
- PARP inhibition in cancer therapy 4
- Inflammatory Biomarkers in Disease Prognosis 2
- Co-authors
- Jin‐Xiong She (12 shared papers)Ashok Sharma (4 shared papers)Shan Bai (4 shared papers)John L. Wagner (1 shared paper)Nathan D. Smith (1 shared paper)Sharad Ghamande (13 shared papers)Bunja Rungruang (11 shared papers)Sharad Purohit (8 shared papers)
- Journals
- Gynecologic Oncology (11 papers)Scientific Reports (1 paper)Nature Communications (1 paper)BMC Pregnancy and Childbirth (1 paper)BMC Cancer (1 paper)
- Partner nations
- United StatesItalyTaiwan
In The Last Decade
David Mysona
25 papers receiving 416 citations
Peers
Comparison fields: 5 of 84
- Cancer Research 112
- Health Informatics 9
- Reproductive Medicine 45
- Obstetrics and Gynecology 39
- Oncology 104
Countries citing papers authored by David Mysona
This map shows the geographic impact of David Mysona'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 David Mysona with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites David Mysona more than expected).
Fields of papers citing papers by David Mysona
This network shows the impact of papers produced by David Mysona. 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 David Mysona. The network helps show where David Mysona may publish in the future.
Co-authors
The 25 scholars most cited alongside David Mysona, 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 | 2019 | 217 | |
| 2 | 2018 | 61 | |
| 3 | 2018 | 25 | |
| 4 | 2021 | 19 | |
| 5 | 2019 | 12 | |
| 6 | 2020 | 11 | |
| 7 | 2020 | 9 | |
| 8 | 2020 | 9 | |
| 9 | 2020 | 8 | |
| 10 | 2017 | 8 | |
| 11 | 2022 | 5 | |
| 12 | 2020 | 5 | |
| 13 | 2023 | 5 | |
| 14 | 2021 | 4 | |
| 15 | 2024 | 4 | |
| 16 | 2020 | 4 | |
| 17 | Tumor-intrinsic and -extrinsic (immune) gene signatures robustly predict overall survival and treatment response in high grade serous ovarian cancer patients. | 2021 | 3 |
| 18 | 2023 | 2 | |
| 19 | 2024 | 2 | |
| 20 | 2023 | 1 |
About David Mysona
David Mysona is a scholar working on Molecular Biology, Oncology, Reproductive Medicine, Obstetrics and Gynecology and Immunology, having authored 25 papers that have together received 419 indexed citations. Recurring topics across this work include Ovarian cancer diagnosis and treatment (8 papers), Endometrial and Cervical Cancer Treatments (5 papers), PARP inhibition in cancer therapy (4 papers), Glycosylation and Glycoproteins Research (3 papers), Cancer Genomics and Diagnostics (3 papers), Galectins and Cancer Biology (2 papers), Inflammatory Biomarkers in Disease Prognosis (2 papers) and Cancer-related molecular mechanisms research (2 papers). The work is most often cited by research in Cancer Research (112 citations), Health Informatics (9 citations), Reproductive Medicine (45 citations), Obstetrics and Gynecology (39 citations) and Oncology (104 citations). David Mysona has collaborated with scholars based in United States, Italy and Taiwan. Frequent co-authors include Jin‐Xiong She, Ashok Sharma, Shan Bai, John L. Wagner, Nathan D. Smith, Sharad Ghamande, Bunja Rungruang, Sharad Purohit, Lynn Tran and Peng George Wang. Their work appears in journals such as Gynecologic Oncology, Scientific Reports, Nature Communications, BMC Pregnancy and Childbirth and BMC Cancer.
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.