Daniel Poon
Impact in
- Health Informatics top 0.5%
- Artificial Intelligence in Healthcare and Education
- Family Practice top 10%
Papers in ⓘ
- Co-authors
- Rohit Srinivasan (3 shared papers)Cherry Sit (1 shared paper)Ashik Amlani (1 shared paper)Keerthini Muthuswamy (1 shared paper)Valerie Ng (1 shared paper)Robert M. Rodriguez (1 shared paper)Jonathan Fortman (1 shared paper)Kristin M. Brinner (1 shared paper)
- Journals
- Bioorganic & Medicinal Chemistry Letters (3 papers)ACS Medicinal Chemistry Letters (2 papers)Cancer Research (2 papers)Annals of Emergency Medicine (1 paper)Insights into Imaging (1 paper)
- Partner nations
- United KingdomSwitzerlandUnited States
In The Last Decade
Daniel Poon
17 papers receiving 526 citations
Peers
Comparison fields: 5 of 87
- Health Informatics 254
- Family Practice 28
- General Dentistry 21
- Radiology, Nuclear Medicine and Imaging 151
- Emergency Medicine 47
Countries citing papers authored by Daniel Poon
This map shows the geographic impact of Daniel Poon'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 Daniel Poon with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel Poon more than expected).
Fields of papers citing papers by Daniel Poon
This network shows the impact of papers produced by Daniel Poon. 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 Daniel Poon. The network helps show where Daniel Poon may publish in the future.
Co-authors
The 25 scholars most cited alongside Daniel Poon, 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 | 2020 | 302 | |
| 2 | 2008 | 76 | |
| 3 | 2015 | 35 | |
| 4 | 2015 | 21 | |
| 5 | 2009 | 20 | |
| 6 | CHIR-265 is a potent selective inhibitor of c-Raf/B-Raf/mutB-Raf that effectively inhibits proliferation and survival of cancer cell lines with Ras/Raf pathway mutations | 2006 | 18 |
| 7 | 2015 | 14 | |
| 8 | 2020 | 13 | |
| 9 | 2014 | 11 | |
| 10 | 2015 | 9 | |
| 11 | 2017 | 8 | |
| 12 | 2020 | 5 | |
| 13 | 2020 | 2 | |
| 14 | 2010 | 2 | |
| 15 | 2019 | 1 | |
| 16 | 2020 | 1 | |
| 17 | 2020 | 1 |
About Daniel Poon
Daniel Poon is a scholar working on Health Informatics, Modeling and Simulation, Organic Chemistry, Computational Theory and Mathematics and Hematology, having authored 17 papers that have together received 539 indexed citations. Recurring topics across this work include Melanoma and MAPK Pathways (9 papers), Synthesis and biological activity (5 papers), Computational Drug Discovery Methods (3 papers), Kidney Stones and Urolithiasis Treatments (2 papers), Radiology practices and education (2 papers), Cancer Immunotherapy and Biomarkers (2 papers), Multiple Myeloma Research and Treatments (2 papers) and Pediatric Urology and Nephrology Studies (2 papers). The work is most often cited by research in Health Informatics (254 citations), Family Practice (28 citations), General Dentistry (21 citations), Radiology, Nuclear Medicine and Imaging (151 citations) and Emergency Medicine (47 citations). Daniel Poon has collaborated with scholars based in United Kingdom, Switzerland and United States. Frequent co-authors include Rohit Srinivasan, Cherry Sit, Ashik Amlani, Keerthini Muthuswamy, Valerie Ng, Robert M. Rodriguez, Jonathan Fortman, Kristin M. Brinner, Wooseok Han and Jeffrey T. Bagdanoff. Their work appears in journals such as Bioorganic & Medicinal Chemistry Letters, ACS Medicinal Chemistry Letters, Cancer Research, Annals of Emergency Medicine and Insights into Imaging.
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.