Adrian Wan
Impact in
- Cancer Research top 5%
- Cancer Genomics and Diagnostics
- Hematology top 10%
- Acute Myeloid Leukemia Research
Papers in
-
- Single-cell and spatial transcriptomics 3
- Ubiquitin and proteasome pathways 2
- Nuclear Structure and Function 1
- Gene expression and cancer classification 1
-
- Cancer Genomics and Diagnostics 3
- Co-authors
- Samuel Aparício (5 shared papers)Damian Yap (4 shared papers)Emma Laks (2 shared papers)Andrew Roth (2 shared papers)Justina Biele (2 shared papers)Alexandre Bouchard‐Côté (2 shared papers)Sohrab P. Shah (3 shared papers)Jaswinder Khattra (1 shared paper)
- Journals
- Nature Methods (2 papers)Blood (2 papers)Annals of Applied Biology (1 paper)Experimental Hematology (1 paper)Science Signaling (1 paper)
- Partner nations
- CanadaUnited KingdomAustralia
In The Last Decade
Adrian Wan
13 papers receiving 1.2k citations
Adrian Wan's Hit Papers
Peers
Comparison fields: 5 of 85
- Cancer Research 499
- Hematology 99
- Molecular Biology 555
- Oncology 202
- Pathology and Forensic Medicine 128
Countries citing papers authored by Adrian Wan
This map shows the geographic impact of Adrian 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 Adrian Wan with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Adrian Wan more than expected).
Fields of papers citing papers by Adrian Wan
This network shows the impact of papers produced by Adrian 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 Adrian Wan. The network helps show where Adrian Wan may publish in the future.
Co-authors
The 25 scholars most cited alongside Adrian 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 | PyClone: statistical inference of clonal population structure in cancer Hit paper breakdown → | 2014 | 587 |
| 2 | 2005 | 209 | |
| 3 | 2012 | 126 | |
| 4 | 2016 | 75 | |
| 5 | 2008 | 49 | |
| 6 | 2006 | 47 | |
| 7 | 2009 | 40 | |
| 8 | 2016 | 40 | |
| 9 | 2005 | 29 | |
| 10 | 2011 | 15 | |
| 11 | 2015 | 14 | |
| 12 | 2010 | 12 | |
| 13 | 2017 | 3 |
About Adrian Wan
Adrian Wan is a scholar working on Molecular Biology, Cancer Research, Hematology, Infectious Diseases and Oncology, having authored 13 papers that have together received 1.2k indexed citations. Recurring topics across this work include Cancer Genomics and Diagnostics (3 papers), Single-cell and spatial transcriptomics (3 papers), Acute Myeloid Leukemia Research (2 papers), Antifungal resistance and susceptibility (2 papers), Ubiquitin and proteasome pathways (2 papers), Nuclear Structure and Function (1 paper), Pancreatic and Hepatic Oncology Research (1 paper) and Gene expression and cancer classification (1 paper). The work is most often cited by research in Cancer Research (499 citations), Hematology (99 citations), Molecular Biology (555 citations), Oncology (202 citations) and Pathology and Forensic Medicine (128 citations). Adrian Wan has collaborated with scholars based in Canada, United Kingdom and Australia. Frequent co-authors include Samuel Aparício, Damian Yap, Emma Laks, Andrew Roth, Justina Biele, Alexandre Bouchard‐Côté, Sohrab P. Shah, Jaswinder Khattra, Gavin Ha and Margo M. Moore. Their work appears in journals such as Nature Methods, Blood, Annals of Applied Biology, Experimental Hematology and Science Signaling.
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.