Jonathan Preall
Impact in
- Cancer Research top 5%
- MicroRNA in disease regulation
- Oncology top 5%
- Cancer Cells and Metastasis
- Pancreatic and Hepatic Oncology Research
Papers in
-
- CRISPR and Genetic Engineering 5
- Single-cell and spatial transcriptomics 4
- RNA Interference and Gene Delivery 3
- RNA regulation and disease 3
- Oncology 6
- Pancreatic and Hepatic Oncology Research 6
- Co-authors
- David A. Tuveson (5 shared papers)B. Czech (6 shared papers)Gregory J. Hannon (6 shared papers)Giulia Biffi (2 shared papers)Youngkyu Park (3 shared papers)Hao Yuan (1 shared paper)Ela Elyada (1 shared paper)Tobiloba E. Oni (1 shared paper)
- Journals
- Proceedings of the National Academy of Sciences (3 papers)Cancer Research (2 papers)Nature Cell Biology (2 papers)Cancer Discovery (2 papers)Molecular Cell (1 paper)
- Partner nations
- United StatesUnited KingdomGermany
In The Last Decade
Jonathan Preall
19 papers receiving 2.3k citations
Jonathan Preall's Hit Papers
Peers
Comparison fields: 5 of 89
- Cancer Research 444
- Oncology 796
- Aging 51
- Immunology 448
- Molecular Biology 1.4k
Countries citing papers authored by Jonathan Preall
This map shows the geographic impact of Jonathan Preall'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 Jonathan Preall with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jonathan Preall more than expected).
Fields of papers citing papers by Jonathan Preall
This network shows the impact of papers produced by Jonathan Preall. 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 Jonathan Preall. The network helps show where Jonathan Preall may publish in the future.
Co-authors
The 25 scholars most cited alongside Jonathan Preall, 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 22 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | IL1-Induced JAK/STAT Signaling Is Antagonized by TGFβ to Shape CAF Heterogeneity in Pancreatic Ductal Adenocarcinoma Hit paper breakdown → | 2018 | 939 |
| 2 | 2009 | 283 | |
| 3 | 2013 | 200 | |
| 4 | 2015 | 175 | |
| 5 | 2015 | 151 | |
| 6 | 2015 | 93 | |
| 7 | 2012 | 72 | |
| 8 | 2019 | 64 | |
| 9 | 2020 | 63 | |
| 10 | 2022 | 54 | |
| 11 | 2019 | 50 | |
| 12 | 2020 | 42 | |
| 13 | 2006 | 36 | |
| 14 | 2011 | 25 | |
| 15 | 2024 | 15 | |
| 16 | 2022 | 11 | |
| 17 | 2023 | 7 | |
| 18 | 2019 | 6 | |
| 19 | 2022 | 1 | |
| 20 | 2026 | 0 |
About Jonathan Preall
Jonathan Preall is a scholar working on Molecular Biology, Oncology, Immunology, Plant Science and Cancer Research, having authored 22 papers that have together received 2.3k indexed citations. Recurring topics across this work include Pancreatic and Hepatic Oncology Research (6 papers), CRISPR and Genetic Engineering (5 papers), Chromosomal and Genetic Variations (4 papers), Single-cell and spatial transcriptomics (4 papers), Cancer Genomics and Diagnostics (3 papers), T-cell and B-cell Immunology (3 papers), RNA Interference and Gene Delivery (3 papers) and RNA regulation and disease (3 papers). The work is most often cited by research in Cancer Research (444 citations), Oncology (796 citations), Aging (51 citations), Immunology (448 citations) and Molecular Biology (1.4k citations). Jonathan Preall has collaborated with scholars based in United States, United Kingdom and Germany. Frequent co-authors include David A. Tuveson, B. Czech, Gregory J. Hannon, Giulia Biffi, Youngkyu Park, Hao Yuan, Ela Elyada, Tobiloba E. Oni, Benjamin Spielman and Jon McGinn. Their work appears in journals such as Proceedings of the National Academy of Sciences, Cancer Research, Nature Cell Biology, Cancer Discovery and Molecular Cell.
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.