Tom Hearn
Impact in
Papers in
-
- Renal and related cancers 3
- Sphingolipid Metabolism and Signaling 3
- Genetics 11
- Genetic and Kidney Cyst Diseases 8
- Genetic Syndromes and Imprinting 6
- Co-authors
- David I. Wilson (10 shared papers)C. Mirella Spalluto (8 shared papers)Neil A. Hanley (6 shared papers)Karen Piper Hanley (4 shared papers)Glenn L. Renforth (3 shared papers)Andrew Berry (2 shared papers)Nane Copin (1 shared paper)Rachel Jennings (1 shared paper)
- Journals
- Journal of Lipid Research (2 papers)Diabetes (2 papers)Gene (1 paper)Molecular Biology of the Cell (1 paper)Chemistry and Physics of Lipids (1 paper)
- Partner nations
- United KingdomUnited StatesGermany
In The Last Decade
Tom Hearn
23 papers receiving 1.4k citations
Peers
Comparison fields: 5 of 78
- Genetics 765
- Surgery 421
- Molecular Biology 653
- Biochemistry 59
- Cell Biology 113
Countries citing papers authored by Tom Hearn
This map shows the geographic impact of Tom Hearn'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 Tom Hearn with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Tom Hearn more than expected).
Fields of papers citing papers by Tom Hearn
This network shows the impact of papers produced by Tom Hearn. 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 Tom Hearn. The network helps show where Tom Hearn may publish in the future.
Co-authors
The 25 scholars most cited alongside Tom Hearn, 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 24 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2002 | 216 | |
| 2 | 2013 | 213 | |
| 3 | 2005 | 176 | |
| 4 | 2007 | 112 | |
| 5 | 2010 | 83 | |
| 6 | 2018 | 78 | |
| 7 | 2004 | 60 | |
| 8 | 1980 | 50 | |
| 9 | 2012 | 48 | |
| 10 | 2003 | 44 | |
| 11 | 2016 | 44 | |
| 12 | 2019 | 43 | |
| 13 | 2013 | 39 | |
| 14 | 2019 | 37 | |
| 15 | 2017 | 35 | |
| 16 | 2002 | 34 | |
| 17 | 2010 | 26 | |
| 18 | 2018 | 24 | |
| 19 | 2010 | 19 | |
| 20 | 2017 | 15 |
About Tom Hearn
Tom Hearn is a scholar working on Molecular Biology, Genetics, Surgery, Oncology and Cell Biology, having authored 24 papers that have together received 1.4k indexed citations. Recurring topics across this work include Genetic and Kidney Cyst Diseases (8 papers), Cholesterol and Lipid Metabolism (7 papers), Genetic Syndromes and Imprinting (6 papers), Drug Transport and Resistance Mechanisms (5 papers), Microtubule and mitosis dynamics (3 papers), Renal and related cancers (3 papers), Sphingolipid Metabolism and Signaling (3 papers) and Pancreatic function and diabetes (3 papers). The work is most often cited by research in Genetics (765 citations), Surgery (421 citations), Molecular Biology (653 citations), Biochemistry (59 citations) and Cell Biology (113 citations). Tom Hearn has collaborated with scholars based in United Kingdom, United States and Germany. Frequent co-authors include David I. Wilson, C. Mirella Spalluto, Neil A. Hanley, Karen Piper Hanley, Glenn L. Renforth, Andrew Berry, Nane Copin, Rachel Jennings, Neil Roberts and William J. Griffiths. Their work appears in journals such as Journal of Lipid Research, Diabetes, Gene, Molecular Biology of the Cell and Chemistry and Physics of Lipids.
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.