Jonathan C. M. Wan
- Cancer Research top 1%
- Cancer Genomics and Diagnostics 9
- Oncology top 5%
- COVID-19 and healthcare impacts 5
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- Renal cell carcinoma treatment 2
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- Genetic factors in colorectal cancer 4
- Molecular Biology top 10%
- Single-cell and spatial transcriptomics 3
- Molecular Biology Techniques and Applications 2
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- Innovations in Medical Education 5
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- Radiomics and Machine Learning in Medical Imaging 2
- Co-authors
- Nitzan RosenfeldJames D. BrentonCarlos CaldasRichard D. BairdCharles MassieJavier García-CorbachoFlorent MoulièreSimon Pacey
- Partner nations
- United KingdomUnited StatesAustralia
In The Last Decade
Jonathan C. M. Wan
21 papers receiving 2.0k citations
Hit Papers
Peers
Comparison fields: 5 of 113
- Cancer Research 1.5k
- Oncology 681
- Pulmonary and Respiratory Medicine 656
- Pathology and Forensic Medicine 357
- Molecular Biology 836
Countries citing papers authored by Jonathan C. M. Wan
This map shows the geographic impact of Jonathan C. M. Wan'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 Jonathan C. M. Wan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jonathan C. M. Wan more than expected).
Fields of papers citing papers by Jonathan C. M. Wan
This network shows the impact of papers produced by Jonathan C. M. Wan. 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 Jonathan C. M. Wan. The network helps show where Jonathan C. M. Wan may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Jonathan C. M. Wan, 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 | 2025 | 0 | |
| 2 | 2025 | 5 | |
| 3 | 2023 | 6 | |
| 4 | 2023 | 6 | |
| 5 | 2023 | 6 | |
| 6 | 2022 | 24 | |
| 7 | 2022 | 2 | |
| 8 | 2021 | 11 | |
| 9 | 2021 | 14 | |
| 10 | 2021 | 26 | |
| 11 | 2021 | 0 | |
| 12 | 2020 | 36 | |
| 13 | 2020 | 15 | |
| 14 | 2020 | 9 | |
| 15 | 2020 | 21 | |
| 16 | Liquid biopsies come of age: towards implementation of circulating tumour DNAbreakdown → | 2017 | 1766 |
| 17 | 2017 | 1 | |
| 18 | 2017 | 6 | |
| 19 | 2008 | 3 | |
| 20 | 1996 | 2 |
About Jonathan C. M. Wan
Jonathan C. M. Wan is a scholar working on Research and Theory, Cancer Research and Pathology and Forensic Medicine, having authored 23 papers that have together received 2.0k indexed citations. Recurring topics across this work include Cancer Genomics and Diagnostics (9 papers), Innovations in Medical Education (5 papers), COVID-19 and healthcare impacts (5 papers), Genetic factors in colorectal cancer (4 papers), Single-cell and spatial transcriptomics (3 papers), Radiomics and Machine Learning in Medical Imaging (2 papers), Renal cell carcinoma treatment (2 papers) and Molecular Biology Techniques and Applications (2 papers). The work is most often cited by research in Cancer Research (1.5k citations), Oncology (681 citations) and Pulmonary and Respiratory Medicine (656 citations). Jonathan C. M. Wan has collaborated with scholars based in United Kingdom, United States and Australia. Frequent co-authors include Nitzan Rosenfeld, James D. Brenton, Carlos Caldas, Richard D. Baird, Charles Massie, Javier García-Corbacho, Florent Moulière, Simon Pacey, Luis A. Díaz and Dana W.Y. Tsui.
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.