Jonathan C. M. Wan

4.7k total citations · 1 hit paper
23 papers, 2.0k citations indexed

About

Jonathan C. M. Wan is a scholar working on Cancer Research, Molecular Biology and Oncology. According to data from OpenAlex, Jonathan C. M. Wan has authored 23 papers receiving a total of 2.0k indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Cancer Research, 6 papers in Molecular Biology and 6 papers in Oncology. Recurrent topics in Jonathan C. M. Wan's work include Cancer Genomics and Diagnostics (9 papers), Innovations in Medical Education (5 papers) and COVID-19 and healthcare impacts (5 papers). Jonathan C. M. Wan is often cited by papers focused on Cancer Genomics and Diagnostics (9 papers), Innovations in Medical Education (5 papers) and COVID-19 and healthcare impacts (5 papers). Jonathan C. M. Wan collaborates with scholars based in United Kingdom, United States and Australia. Jonathan C. M. Wan's 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 and has published in prestigious journals such as The Lancet, Nature Communications and Nature reviews. Cancer.

In The Last Decade

Jonathan C. M. Wan

21 papers receiving 2.0k citations

Hit Papers

Liquid biopsies come of age: towards implementation of ci... 2017 2026 2020 2023 2017 500 1000 1.5k
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Liquid biopsies come of age: towards implementation of circulating tumour DNA
    2017 1.8k citations Jonathan C. M. Wan, Charles Massie et al. Nature reviews. Cancer profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Jonathan C. M. Wan United Kingdom 10 1.5k 836 681 656 357 23 2.0k
Heather Biggs United Kingdom 7 1.7k 1.1× 727 0.9× 832 1.2× 821 1.3× 450 1.3× 12 2.0k
Javier García-Corbacho Spain 15 1.5k 1.0× 887 1.1× 1.1k 1.5× 800 1.2× 395 1.1× 44 2.3k
Francesco Marass United Kingdom 12 1.6k 1.1× 848 1.0× 834 1.2× 861 1.3× 362 1.0× 20 2.1k
AmirAli Talasaz United States 17 1.5k 1.0× 625 0.7× 1.2k 1.7× 900 1.4× 501 1.4× 106 2.3k
Katherine A. Thornton United States 19 1.8k 1.2× 868 1.0× 1.3k 1.8× 1.3k 2.0× 653 1.8× 68 3.1k
Alvin Wong Singapore 14 1.2k 0.8× 617 0.7× 917 1.3× 809 1.2× 281 0.8× 39 1.9k
Anna Piskorz United Kingdom 17 1.6k 1.1× 1.1k 1.3× 1.0k 1.5× 749 1.1× 502 1.4× 34 2.7k
Iain Beehuat Tan Singapore 20 748 0.5× 1.2k 1.4× 878 1.3× 408 0.6× 268 0.8× 72 2.2k
Mohit Butaney United States 19 894 0.6× 892 1.1× 1.5k 2.2× 1.8k 2.8× 266 0.7× 68 2.7k
David L. Wachter Germany 23 530 0.4× 696 0.8× 498 0.7× 227 0.3× 334 0.9× 59 1.8k

Countries citing papers authored by Jonathan C. M. Wan

Since Specialization
Citations

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

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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 of co-authors of Jonathan C. M. Wan

This figure shows the co-authorship network connecting the top 25 collaborators of Jonathan C. M. Wan. A scholar is included among the top collaborators of Jonathan C. M. Wan based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Jonathan C. M. Wan. Jonathan C. M. Wan is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
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Wan, Jonathan C. M., Peter Sasieni, & Nitzan Rosenfeld. (2025). Promises and pitfalls of multi-cancer early detection using liquid biopsy tests. Nature Reviews Clinical Oncology. 22(8). 566–580. 5 indexed citations
3.
Byrne, Matthew H V, James Ashcroft, Jonathan C. M. Wan, et al.. (2023). Examining medical student volunteering during the COVID-19 pandemic as a prosocial behaviour during an emergency. Postgraduate Medical Journal. 99(1174). 883–893. 6 indexed citations
4.
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Shoaie, Saeed, et al.. (2023). Leveraging circulating microbial DNA for early cancer detection. Trends in cancer. 9(11). 879–882. 6 indexed citations
6.
Wan, Jonathan C. M., Dennis Stephens, James R. White, et al.. (2022). Genome-wide mutational signatures in low-coverage whole genome sequencing of cell-free DNA. Nature Communications. 13(1). 4953–4953. 24 indexed citations
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Byrne, Matthew H V, et al.. (2021). Systematic review of medical student willingness to volunteer and preparedness for pandemics and disasters. Emergency Medicine Journal. 39(10). e6–e6. 11 indexed citations
9.
Byrne, Matthew H V, James Ashcroft, Laith Alexander, et al.. (2021). COVIDReady2 study protocol: cross-sectional survey of medical student volunteering and education during the COVID-19 pandemic in the United Kingdom. BMC Medical Education. 21(1). 14 indexed citations
10.
Wan, Jonathan C. M., Tariq I. Mughal, Pedram Razavi, et al.. (2021). Liquid biopsies for residual disease and recurrence. Med. 2(12). 1292–1313. 26 indexed citations
11.
Byrne, Matthew H V, James Ashcroft, Laith Alexander, et al.. (2021). P78 MedEd Collaborative: a new research collaborative to promote medical education research. BJS Open. 5(Supplement_1).
12.
Heider, Katrin, Jonathan C. M. Wan, James Hall, et al.. (2020). Detection of ctDNA from Dried Blood Spots after DNA Size Selection. Clinical Chemistry. 66(5). 697–705. 36 indexed citations
13.
Wan, Jonathan C. M.. (2020). Survival Outcomes of Early versus Deferred Cystectomy for High-Grade Non-Muscle-Invasive Bladder Cancer: A Systematic Review. Current Urology. 14(2). 66–73. 15 indexed citations
14.
Alexander, Laith, James Ashcroft, Matthew H V Byrne, & Jonathan C. M. Wan. (2020). All hands on deck: early graduation of senior medical students in the COVID-19 pandemic. MedEdPublish. 9. 96–96. 9 indexed citations
15.
Gill, Andrew B., Leonardo Rundo, Jonathan C. M. Wan, et al.. (2020). Correlating Radiomic Features of Heterogeneity on CT with Circulating Tumor DNA in Metastatic Melanoma. Cancers. 12(12). 3493–3493. 21 indexed citations
16.
Wan, Jonathan C. M., Charles Massie, Javier García-Corbacho, et al.. (2017). Liquid biopsies come of age: towards implementation of circulating tumour DNA. Nature reviews. Cancer. 17(4). 223–238. 1766 indexed citations breakdown →
17.
Wan, Jonathan C. M., Suzanne Murphy, Davina Gale, et al.. (2017). Individualised monitoring of patients with metastatic melanoma using plasma DNA. The Lancet. 389. S99–S99. 1 indexed citations
18.
Ahmed, Faheem, et al.. (2017). Student-led leadership training for undergraduate healthcare students. Leadership in health services. 30(4). 428–431. 6 indexed citations
19.
Jenkins, Christine, et al.. (2008). Application of Radial Symmetry for Caldera Detection. 142–147. 3 indexed citations
20.

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.

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