Bryan W. Day
Impact in
- Genetics top 1%
- Glioma Diagnosis and Treatment
- Cancer Research top 2%
- MicroRNA in disease regulation
- Cancer, Hypoxia, and Metabolism
Papers in
-
- DNA Repair Mechanisms 7
- Angiogenesis and VEGF in Cancer 5
- Genetics 34
- Glioma Diagnosis and Treatment 34
- Co-authors
- Brett W. Stringer (39 shared papers)Andy Boyd (27 shared papers)Benjamin Chua (4 shared papers)Chamindie Punyadeera (4 shared papers)Juliana Müller Bark (4 shared papers)Arutha Kulasinghe (2 shared papers)Terrance G. Johns (15 shared papers)Kathleen S. Ensbey (11 shared papers)
- Journals
- Neuro-Oncology (6 papers)Journal of Neuro-Oncology (4 papers)Cancers (4 papers)British Journal of Cancer (3 papers)Oncotarget (3 papers)
- Partner nations
- AustraliaUnited StatesGermany
In The Last Decade
Bryan W. Day
78 papers receiving 2.4k citations
Peers
Comparison fields: 5 of 102
- Genetics 630
- Cancer Research 595
- Oncology 546
- Molecular Biology 1.3k
- Cell Biology 297
Countries citing papers authored by Bryan W. Day
This map shows the geographic impact of Bryan W. Day'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 Bryan W. Day with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Bryan W. Day more than expected).
Fields of papers citing papers by Bryan W. Day
This network shows the impact of papers produced by Bryan W. Day. 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 Bryan W. Day. The network helps show where Bryan W. Day may publish in the future.
Co-authors
The 25 scholars most cited alongside Bryan W. Day, 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 82 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2013 | 382 | |
| 2 | 2019 | 188 | |
| 3 | 2013 | 109 | |
| 4 | 2018 | 91 | |
| 5 | 2012 | 77 | |
| 6 | 2011 | 75 | |
| 7 | 2019 | 75 | |
| 8 | 2016 | 69 | |
| 9 | 2017 | 65 | |
| 10 | 2014 | 62 | |
| 11 | 2014 | 62 | |
| 12 | 2014 | 51 | |
| 13 | 2017 | 49 | |
| 14 | 2017 | 45 | |
| 15 | 2015 | 44 | |
| 16 | TAXOL: A UNIQUE ANTIEOPLASTIC AGENT WITH SIGNIFICANT ACTIVITY IN ADVANCED OVARION EPITHELIAL NEOPLASM | 1996 | 41 |
| 17 | 2015 | 39 | |
| 18 | 2010 | 39 | |
| 19 | 2021 | 38 | |
| 20 | 2019 | 37 |
About Bryan W. Day
Bryan W. Day is a scholar working on Molecular Biology, Genetics, Cancer Research, Cellular and Molecular Neuroscience and Oncology, having authored 82 papers that have together received 2.5k indexed citations. Recurring topics across this work include Glioma Diagnosis and Treatment (34 papers), Axon Guidance and Neuronal Signaling (12 papers), DNA Repair Mechanisms (7 papers), Neurogenesis and neuroplasticity mechanisms (5 papers), Microtubule and mitosis dynamics (5 papers), Cancer Cells and Metastasis (5 papers), Hippo pathway signaling and YAP/TAZ (5 papers) and Angiogenesis and VEGF in Cancer (5 papers). The work is most often cited by research in Genetics (630 citations), Cancer Research (595 citations), Oncology (546 citations), Molecular Biology (1.3k citations) and Cell Biology (297 citations). Bryan W. Day has collaborated with scholars based in Australia, United States and Germany. Frequent co-authors include Brett W. Stringer, Andy Boyd, Benjamin Chua, Chamindie Punyadeera, Juliana Müller Bark, Arutha Kulasinghe, Terrance G. Johns, Kathleen S. Ensbey, Jann N. Sarkaria and Yuchen Li. Their work appears in journals such as Neuro-Oncology, Journal of Neuro-Oncology, Cancers, British Journal of Cancer and Oncotarget.
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.