Tom V. Lee
Impact in
- Cell Biology top 10%
- Hippo pathway signaling and YAP/TAZ
Papers in
-
- Developmental Biology and Gene Regulation 7
- Cell death mechanisms and regulation 4
- Ubiquitin and proteasome pathways 3
- Kruppel-like factors research 2
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- Hippo pathway signaling and YAP/TAZ 3
- Co-authors
- Andreas Bergmann (7 shared papers)Hamed Jafar‐Nejad (7 shared papers)Michael B. Elowitz (2 shared papers)Yun Fan (2 shared papers)Lauren LeBon (2 shared papers)David Sprinzak (2 shared papers)Clare Bolduc (3 shared papers)Sarah E. Woodfield (1 shared paper)
- Journals
- PLoS Genetics (5 papers)Cell Reports (2 papers)Development (2 papers)eLife (2 papers)Alzheimer s & Dementia (1 paper)
- Partner nations
- United StatesUnited KingdomGermany
In The Last Decade
Tom V. Lee
20 papers receiving 690 citations
Peers
Comparison fields: 5 of 77
- Cell Biology 166
- Aging 16
- Molecular Biology 540
- Immunology 149
- Cellular and Molecular Neuroscience 66
Countries citing papers authored by Tom V. Lee
This map shows the geographic impact of Tom V. Lee'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 V. Lee with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Tom V. Lee more than expected).
Fields of papers citing papers by Tom V. Lee
This network shows the impact of papers produced by Tom V. Lee. 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 V. Lee. The network helps show where Tom V. Lee may publish in the future.
Co-authors
The 25 scholars most cited alongside Tom V. Lee, 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 | 2014 | 110 | |
| 2 | 2009 | 96 | |
| 3 | 2008 | 91 | |
| 4 | 2013 | 78 | |
| 5 | 2007 | 55 | |
| 6 | 2005 | 53 | |
| 7 | 2011 | 40 | |
| 8 | 2014 | 30 | |
| 9 | 2019 | 28 | |
| 10 | 2005 | 23 | |
| 11 | 2017 | 23 | |
| 12 | 2022 | 14 | |
| 13 | 2018 | 11 | |
| 14 | 2000 | 10 | |
| 15 | 2010 | 8 | |
| 16 | 2023 | 7 | |
| 17 | 2019 | 6 | |
| 18 | Helper peptide G89 (HER-2:777-789) and G89-activated cells regulate the survival of effectors induced by the CTL epitope E75 (HER-2, 369-377). Correlation with the IFN-gamma: IL-10 balance. | 2002 | 5 |
| 19 | 2014 | 2 | |
| 20 | 2017 | 1 |
About Tom V. Lee
Tom V. Lee is a scholar working on Molecular Biology, Cell Biology, Immunology, Oncology and Cellular and Molecular Neuroscience, having authored 20 papers that have together received 691 indexed citations. Recurring topics across this work include Developmental Biology and Gene Regulation (7 papers), Invertebrate Immune Response Mechanisms (4 papers), Cell death mechanisms and regulation (4 papers), Hippo pathway signaling and YAP/TAZ (3 papers), Ubiquitin and proteasome pathways (3 papers), Kruppel-like factors research (2 papers), Neurobiology and Insect Physiology Research (2 papers) and Cancer-related Molecular Pathways (2 papers). The work is most often cited by research in Cell Biology (166 citations), Aging (16 citations), Molecular Biology (540 citations), Immunology (149 citations) and Cellular and Molecular Neuroscience (66 citations). Tom V. Lee has collaborated with scholars based in United States, United Kingdom and Germany. Frequent co-authors include Andreas Bergmann, Hamed Jafar‐Nejad, Michael B. Elowitz, Yun Fan, Lauren LeBon, David Sprinzak, Clare Bolduc, Sarah E. Woodfield, Christian Antonio and Dongbin Xu. Their work appears in journals such as PLoS Genetics, Cell Reports, Development, eLife and Alzheimer s & Dementia.
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.