Tony Pawson
- Cell Biology top 0.01%
- Hippo pathway signaling and YAP/TAZ 29
- Immunology and Allergy top 0.05%
- Cell Adhesion Molecules Research 32
- Molecular Biology top 0.01%
- Protein Kinase Regulation and GTPase Signaling 107
- Protein Tyrosine Phosphatases 51
- PI3K/AKT/mTOR signaling in cancer 49
- Ubiquitin and proteasome pathways 38
- Immunology top 0.05%
- Cellular and Molecular Neuroscience top 0.05%
- Axon Guidance and Neuronal Signaling 41
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- Monoclonal and Polyclonal Antibodies Research 47
- Co-authors
- John D. ScottGerald GishChristine EllisPiers NashMichael F. MoranJane McGladeGeraldine MbamaluJulie D. Forman‐Kay
- Partner nations
- CanadaUnited StatesGermany
In The Last Decade
Tony Pawson
446 papers receiving 67.3k citations
Hit Papers
Peers
Comparison fields: 5 of 187
- Cell Biology 13.1k
- Immunology and Allergy 4.6k
- Molecular Biology 49.8k
- Immunology 9.8k
- Cellular and Molecular Neuroscience 8.2k
Countries citing papers authored by Tony Pawson
This map shows the geographic impact of Tony Pawson'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 Tony Pawson with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Tony Pawson more than expected).
Fields of papers citing papers by Tony Pawson
This network shows the impact of papers produced by Tony Pawson. 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 Tony Pawson. The network helps show where Tony Pawson may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Tony Pawson, 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 | 2017 | 37 | |
| 2 | Histone Recognition and Large-Scale Structural Analysis of the Human Bromodomain Familybreakdown → | 2012 | 1230 |
| 3 | 2011 | 75 | |
| 4 | 2010 | 24 | |
| 5 | A Global Protein Kinase and Phosphatase Interaction Network in Yeastbreakdown → | 2010 | 512 |
| 6 | 2010 | 46 | |
| 7 | 2009 | 190 | |
| 8 | 2009 | 78 | |
| 9 | 2008 | 98 | |
| 10 | 2007 | 198 | |
| 11 | 2007 | 34 | |
| 12 | Dissecting virulence: Systematic and functional analyses of a pathogenicity islandbreakdown → | 2004 | 511 |
| 13 | 1995 | 51 | |
| 14 | 1995 | 61 | |
| 15 | Shc products are substrates of erbB-2 kinase. | 1993 | 99 |
| 16 | 1993 | 31 | |
| 17 | 1991 | 10 | |
| 18 | 1991 | 16 | |
| 19 | 1990 | 39 | |
| 20 | 1985 | 25 |
About Tony Pawson
Tony Pawson is a scholar working on Cell Biology, Immunology and Allergy and Molecular Biology, having authored 447 papers that have together received 68.5k indexed citations. Recurring topics across this work include Protein Kinase Regulation and GTPase Signaling (107 papers), Protein Tyrosine Phosphatases (51 papers), PI3K/AKT/mTOR signaling in cancer (49 papers), Monoclonal and Polyclonal Antibodies Research (47 papers), Axon Guidance and Neuronal Signaling (41 papers), Ubiquitin and proteasome pathways (38 papers), Cell Adhesion Molecules Research (32 papers) and Hippo pathway signaling and YAP/TAZ (29 papers). The work is most often cited by research in Cell Biology (13.1k citations), Immunology and Allergy (4.6k citations) and Molecular Biology (49.8k citations). Tony Pawson has collaborated with scholars based in Canada, United States and Germany. Frequent co-authors include John D. Scott, Gerald Gish, Christine Ellis, Piers Nash, Michael F. Moran, Jane McGlade, Geraldine Mbamalu, Julie D. Forman‐Kay, Christine Koch and Mark Henkemeyer. Their work appears in journals such as Nature, Science and 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.