John V. Pearson

58 papers receiving 3.6k citations

John V. Pearson's Hit Papers

Deep learning in cancer diagnosis, prognosis and treatment selection 2021 · 524 citations
5240+6+12Years since publication250500750

Peers

John V. Pearson
Comparison fields: 5 of 161
  • Health Informatics 76
  • Cancer Research 659
  • Genetics 745
  • Molecular Biology 1.8k
  • Oncology 566
Replace Pingzhao Hu with:
Pingzhao Hu Canada
Casey S. Greene United States
Saurabh Saha United States
Nicola Waddell Australia
Daniele Merico Canada
Mikael Lundin Finland
Michael Krauthammer United States
James C. Costello United States
Suzanne D. Conzen United States
Maciej Wiznerowicz Poland
John V. Pearson relative to Pingzhao Hu Canada Pingzhao Hu's profile →
Citations per field
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Pingzhao Hu · 1×
Citations per year

Countries citing papers authored by John V. Pearson

Since Specialization
Citations

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

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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.

Border = papers with John V. Pearson Line = papers co-authored together John V. Pearson links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

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 →
2008757
2
Deep learning in cancer diagnosis, prognosis and treatment selection
Hit paper breakdown →
2021524
3 2006312
4 2011258
5 2008238
6 2015234
7 2007154
8 1996145
9 2010134
10 199983
11 200761
12 201752
13 201544
14 200843
15 201942
16 202142
17 200639
18 202338
19 201937
20 201134

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.

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