John V. Pearson
Impact in
- Health Informatics top 2%
- Cancer Research top 2%
- Cancer Genomics and Diagnostics
Papers in
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- Single-cell and spatial transcriptomics 5
-
- Cancer Genomics and Diagnostics 21
- Co-authors
- Nicola Waddell (33 shared papers)David W. Craig (9 shared papers)Szabolcs Szelinger (4 shared papers)Dietrich A. Stephan (3 shared papers)Nils Homer (3 shared papers)Olga Kondrashova (7 shared papers)Khoa Tran (3 shared papers)Elizabeth D. Williams (2 shared papers)
- Journals
- Scientific Reports (3 papers)Cancers (3 papers)Journal of Endocrinology (3 papers)Bioinformatics (2 papers)Nucleic Acids Research (2 papers)
- Partner nations
- AustraliaUnited StatesUnited Kingdom
In The Last Decade
John V. Pearson
58 papers receiving 3.6k citations
John V. Pearson's Hit Papers
Peers
Comparison fields: 5 of 161
- Health Informatics 76
- Cancer Research 659
- Genetics 745
- Molecular Biology 1.8k
- Oncology 566
Countries citing papers authored by John V. Pearson
This map shows the geographic impact of John V. Pearson'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 John V. Pearson with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites John V. Pearson more than expected).
Fields of papers citing papers by John V. Pearson
This network shows the impact of papers produced by John V. Pearson. 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 John V. Pearson. The network helps show where John V. Pearson may publish in the future.
Co-authors
The 25 scholars most cited alongside John V. Pearson, 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 59 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Resolving Individuals Contributing Trace Amounts of DNA to Highly Complex Mixtures Using High-Density SNP Genotyping Microarrays Hit paper breakdown → | 2008 | 757 |
| 2 | Deep learning in cancer diagnosis, prognosis and treatment selection Hit paper breakdown → | 2021 | 524 |
| 3 | 2006 | 312 | |
| 4 | 2011 | 258 | |
| 5 | 2008 | 238 | |
| 6 | 2015 | 234 | |
| 7 | 2007 | 154 | |
| 8 | 1996 | 145 | |
| 9 | 2010 | 134 | |
| 10 | 1999 | 83 | |
| 11 | 2007 | 61 | |
| 12 | 2017 | 52 | |
| 13 | 2015 | 44 | |
| 14 | 2008 | 43 | |
| 15 | 2019 | 42 | |
| 16 | 2021 | 42 | |
| 17 | 2006 | 39 | |
| 18 | 2023 | 38 | |
| 19 | 2019 | 37 | |
| 20 | 2011 | 34 |
About John V. Pearson
John V. Pearson is a scholar working on Molecular Biology, Cancer Research, Oncology, Genetics and Pulmonary and Respiratory Medicine, having authored 59 papers that have together received 3.7k indexed citations. Recurring topics across this work include Cancer Genomics and Diagnostics (21 papers), Cutaneous Melanoma Detection and Management (6 papers), Genetic factors in colorectal cancer (5 papers), Genetic Associations and Epidemiology (5 papers), Single-cell and spatial transcriptomics (5 papers), Genomic variations and chromosomal abnormalities (4 papers), Pancreatic and Hepatic Oncology Research (4 papers) and Genomics and Rare Diseases (4 papers). The work is most often cited by research in Health Informatics (76 citations), Cancer Research (659 citations), Genetics (745 citations), Molecular Biology (1.8k citations) and Oncology (566 citations). John V. Pearson has collaborated with scholars based in Australia, United States and United Kingdom. Frequent co-authors include Nicola Waddell, David W. Craig, Szabolcs Szelinger, Dietrich A. Stephan, Nils Homer, Olga Kondrashova, Khoa Tran, Elizabeth D. Williams, Andrew P. Bradley and Waibhav Tembe. Their work appears in journals such as Scientific Reports, Cancers, Journal of Endocrinology, Bioinformatics and Nucleic Acids Research.
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.