Jon Travers
Impact in
- Oncology top 10%
- PARP inhibition in cancer therapy
- Cancer-related Molecular Pathways
- Cancer Immunotherapy and Biomarkers
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- DNA Repair Mechanisms
- CRISPR and Genetic Engineering
- Heat shock proteins research
- Ubiquitin and proteasome pathways
Papers in ⓘ
-
- Protein Degradation and Inhibitors 4
- Oncology 13
- Cancer-related Molecular Pathways 4
- CAR-T cell therapy research 3
- PARP inhibition in cancer therapy 2
- Co-authors
- Paul Workman (5 shared papers)Swee Y. Sharp (1 shared paper)Stephen P. Jackson (2 shared papers)Satpal S. Jhujh (1 shared paper)Qian Wu (1 shared paper)Carol V. Robinson (1 shared paper)Shahid Mehmood (1 shared paper)Julia Coates (1 shared paper)
- Journals
- Blood (4 papers)Molecular Cancer Therapeutics (3 papers)Cancer Research (3 papers)Cell Death and Disease (2 papers)Nature Communications (2 papers)
- Partner nations
- United KingdomUnited StatesAustralia
In The Last Decade
Jon Travers
21 papers receiving 651 citations
Peers
Comparison fields: 5 of 82
- Oncology 270
- Molecular Biology 501
- Cancer Research 80
- Computational Theory and Mathematics 63
- Cell Biology 53
Countries citing papers authored by Jon Travers
This map shows the geographic impact of Jon Travers'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 Jon Travers with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jon Travers more than expected).
Fields of papers citing papers by Jon Travers
This network shows the impact of papers produced by Jon Travers. 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 Jon Travers. The network helps show where Jon Travers may publish in the future.
Co-authors
The 25 scholars most cited alongside Jon Travers, 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 23 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | 2015 | 237 | |
| 2 | 2021 | 84 | |
| 3 | 2011 | 84 | |
| 4 | 2007 | 66 | |
| 5 | 2015 | 62 | |
| 6 | 2018 | 50 | |
| 7 | 2013 | 17 | |
| 8 | 2023 | 14 | |
| 9 | 2021 | 10 | |
| 10 | 2010 | 7 | |
| 11 | 2011 | 5 | |
| 12 | 2024 | 4 | |
| 13 | 2022 | 4 | |
| 14 | 2019 | 4 | |
| 15 | 2019 | 4 | |
| 16 | 2025 | 2 | |
| 17 | 2016 | 1 | |
| 18 | 2018 | 1 | |
| 19 | 2015 | 1 | |
| 20 | 2019 | 1 |
About Jon Travers
Jon Travers is a scholar working on Molecular Biology, Oncology, Cell Biology, Hematology and Genetics, having authored 23 papers that have together received 659 indexed citations. Recurring topics across this work include Microtubule and mitosis dynamics (9 papers), Protein Degradation and Inhibitors (4 papers), Acute Myeloid Leukemia Research (4 papers), Cancer-related Molecular Pathways (4 papers), Virus-based gene therapy research (3 papers), CAR-T cell therapy research (3 papers), Plant nutrient uptake and metabolism (2 papers) and PARP inhibition in cancer therapy (2 papers). The work is most often cited by research in Oncology (270 citations), Molecular Biology (501 citations), Cancer Research (80 citations), Computational Theory and Mathematics (63 citations) and Cell Biology (53 citations). Jon Travers has collaborated with scholars based in United Kingdom, United States and Australia. Frequent co-authors include Paul Workman, Swee Y. Sharp, Stephen P. Jackson, Satpal S. Jhujh, Qian Wu, Carol V. Robinson, Shahid Mehmood, Julia Coates, Takashi Ochi and Naoka Tamura. Their work appears in journals such as Blood, Molecular Cancer Therapeutics, Cancer Research, Cell Death and Disease and Nature Communications.
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.