Tony Pawson

555 total papers · 91.5k total citations
447 papers, 68.4k citations indexed

About

Tony Pawson is a scholar working on Molecular Biology, Cell Biology and Oncology. According to data from OpenAlex, Tony Pawson has authored 447 papers receiving a total of 68.4k indexed citations (citations by other indexed papers that have themselves been cited), including 335 papers in Molecular Biology, 88 papers in Cell Biology and 86 papers in Oncology. Recurrent topics in Tony Pawson's work include Protein Kinase Regulation and GTPase Signaling (107 papers), Protein Tyrosine Phosphatases (51 papers) and PI3K/AKT/mTOR signaling in cancer (49 papers). Tony Pawson is often cited by papers focused on Protein Kinase Regulation and GTPase Signaling (107 papers), Protein Tyrosine Phosphatases (51 papers) and PI3K/AKT/mTOR signaling in cancer (49 papers). Tony Pawson collaborates with scholars based in Canada, United States and Germany. Tony Pawson's 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 and has published in prestigious journals such as Nature, Science and Cell.

In The Last Decade

Tony Pawson

446 papers receiving 67.1k citations

Hit Papers

Protein modules and signa... 1986 2026 1999 2012 1995 1994 1997 1991 2015 500 1000 1.5k 2.0k
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation benchmark for papers published in the same subfield and year, or reaches the top citation threshold in at least one of its specific research topics.

  1. Protein modules and signalling networks
    1995 2.0k citations Tony Pawson Nature profile →
  2. Backbone Dynamics of a Free and a Phosphopeptide-Complexed Src Homology 2 Domain Studied by 15N NMR Relaxation
    1994 1.9k citations Neil A. Farrow, Ranjith Muhandiram et al. Biochemistry profile →
  3. Signaling Through Scaffold, Anchoring, and Adaptor Proteins
    1997 1.8k citations Tony Pawson, John D. Scott Science profile →
  4. SH2 and SH3 Domains: Elements that Control Interactions of Cytoplasmic Signaling Proteins
    1991 1.7k citations Christine Koch, Deborah H. Anderson et al. Science profile →
  5. Phase Transition of a Disordered Nuage Protein Generates Environmentally Responsive Membraneless Organelles
    2015 1.3k citations Timothy J. Nott, Evangelia Petsalaki et al. Molecular Cell profile →
  6. Histone Recognition and Large-Scale Structural Analysis of the Human Bromodomain Family
    2012 1.2k citations P. Filippakopoulos, S. Picaud et al. Cell profile →
  7. A novel transforming protein (SHC) with an SH2 domain is implicated in mitogenic signal transduction
    1992 1.2k citations Giuliana Pelicci, Luisa Lanfrancone et al. Cell profile →
  8. Assembly of Cell Regulatory Systems Through Protein Interaction Domains
    2003 1.1k citations Tony Pawson, Piers Nash Science profile →
  9. The SH2 and SH3 domains of mammalian Grb2 couple the EGF receptor to the Ras activator mSos1
    1993 913 citations Maria Rozakis-Adcock, Ross T. Fernley et al. Nature profile →
  10. Association of the Shc and Grb2/Sem5 SH2-containing proteins is implicated in activation of the Ras pathway by tyrosine kinases
    1992 892 citations Maria Rozakis-Adcock, Jane McGlade et al. Nature profile →
  11. β-Catenin and TCF Mediate Cell Positioning in the Intestinal Epithelium by Controlling the Expression of EphB/EphrinB
    2002 889 citations Eduard Batlle, Jeffrey T. Henderson et al. Cell profile →
  12. SH2 and SH3 domains: From structure to function
    1992 873 citations Tony Pawson, Gerald Gish Cell profile →
  13. Specific motifs recognized by the SH2 domains of Csk, 3BP2, fps/fes, GRB-2, HCP, SHC, Syk, and Vav.
    1994 799 citations Zhou Songyang, Steven E. Shoelson et al. Molecular and Cellular Biology profile →
  14. The Discoidin Domain Receptor Tyrosine Kinases Are Activated by Collagen
    1997 793 citations Wolfgang F. Vogel, Gerald Gish et al. Molecular Cell profile →
  15. Eph Receptors and Ligands Comprise Two Major Specificity Subclasses and Are Reciprocally Compartmentalized during Embryogenesis
    1996 730 citations Nicholas W. Gale, Sacha J. Holland et al. Neuron profile →
  16. Phosphorylation of GAP and GAP-associated proteins by transforming and mitogenic tyrosine kinases
    1990 690 citations Christine Ellis, Michael F. Moran et al. Nature profile →
  17. Early Lineage Segregation between Epiblast and Primitive Endoderm in Mouse Blastocysts through the Grb2-MAPK Pathway
    2006 682 citations Claire Chazaud, Yojiro Yamanaka et al. Developmental Cell profile →
  18. Specificity in Signal Transduction
    2004 644 citations Tony Pawson Cell profile →
  19. Post-translational modifications in signal integration
    2010 629 citations Yonathan Lissanu Deribe, Tony Pawson et al. Nature Structural & Molecular Biology profile →
  20. Multisite phosphorylation of a CDK inhibitor sets a threshold for the onset of DNA replication
    2001 628 citations Piers Nash, Xiaojing Tang et al. Nature profile →
  21. A mammalian PAR-3–PAR-6 complex implicated in Cdc42/Rac1 and aPKC signalling and cell polarity
    2000 622 citations Dan Lin, A. Edwards et al. Nature Cell Biology profile →
  22. Ligands for EPH-Related Receptor Tyrosine Kinases that Require Membrane Attachment or Clustering for Activity
    1994 610 citations Samuel Davis, Nicholas W. Gale et al. Science profile →
  23. SH2 and SH3 domains
    1993 593 citations Tony Pawson et al. Current Biology profile →
  24. SH2-Containing Phosphotyrosine Phosphatase as a Target of Protein-Tyrosine Kinases
    1993 587 citations Gen‐Sheng Feng, Tony Pawson et al. Science profile →
  25. ICOS is essential for effective T-helper-cell responses
    2001 558 citations Agostino Tafuri, Arda Shahinian et al. Nature profile →
  26. Dynamic modularity in protein interaction networks predicts breast cancer outcome
    2009 543 citations Ian W. Taylor, Rune Linding et al. Nature Biotechnology profile →
  27. Protein phosphorylation in signaling – 50 years and counting
    2005 537 citations Tony Pawson, John D. Scott Trends in Biochemical Sciences profile →
  28. Syk tyrosine kinase required for mouse viability and B-cell development
    1995 534 citations Alec M. Cheng, Bruce R. Rowley et al. Nature profile →
  29. Binding of SH2 Domains of Phospholipase Cγ1, GAP, and Src to Activated Growth Factor Receptors
    1990 530 citations Deborah H. Anderson, Christine Koch et al. Science profile →
  30. Reading protein modifications with interaction domains
    2006 519 citations Bruce T. Seet, Ivan Đikić et al. Nature Reviews Molecular Cell Biology profile →
  31. A Global Protein Kinase and Phosphatase Interaction Network in Yeast
    2010 511 citations Hyungwon Choi, Brett Larsen et al. Science profile →
  32. Dissecting virulence: Systematic and functional analyses of a pathogenicity island
    2004 511 citations Wanyin Deng, Samantha Gruenheid et al. Proceedings of the National Academy of Sciences profile →
  33. A Noncatalytic Domain Conserved among Cytoplasmic Protein-Tyrosine Kinases Modifies the Kinase Function and Transforming Activity of Fujinami Sarcoma Virus P130gag-fps
    1986 396 citations Ivan Sadowski, James C. Stone et al. Molecular and Cellular Biology profile →

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author Last Decade Papers Cites
Tony Pawson 49.8k 13.1k 10.9k 9.8k 8.1k 447 68.4k
Tony Hunter 77.6k 1.6× 17.5k 1.3× 23.3k 2.1× 11.8k 1.2× 6.8k 0.8× 504 103.7k
Joseph Schlessinger 68.1k 1.4× 16.4k 1.3× 25.0k 2.3× 12.6k 1.3× 7.5k 0.9× 531 96.4k
Philip Cohen 67.5k 1.4× 13.5k 1.0× 9.8k 0.9× 8.8k 0.9× 7.6k 0.9× 490 89.1k
Joan S. Brugge 25.6k 0.5× 9.5k 0.7× 10.2k 0.9× 5.2k 0.5× 2.0k 0.2× 258 41.8k
Ruedi Aebersold 86.5k 1.7× 9.8k 0.7× 9.0k 0.8× 8.5k 0.9× 3.1k 0.4× 783 117.3k
Harvey F. Lodish 49.1k 1.0× 12.2k 0.9× 9.4k 0.9× 8.7k 0.9× 2.2k 0.3× 645 82.0k
John C. Reed 73.3k 1.5× 10.1k 0.8× 21.4k 2.0× 20.4k 2.1× 6.2k 0.8× 797 107.4k
Joseph L. Goldstein 51.8k 1.0× 14.1k 1.1× 8.6k 0.8× 9.2k 0.9× 3.1k 0.4× 405 100.0k
Michael S. Brown 47.8k 1.0× 13.1k 1.0× 7.8k 0.7× 8.9k 0.9× 2.9k 0.4× 375 92.4k
Philip Leder 41.1k 0.8× 6.2k 0.5× 11.8k 1.1× 13.7k 1.4× 1.7k 0.2× 354 63.5k

Countries citing papers authored by Tony Pawson

Since Specialization
Citations

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

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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 of co-authors of Tony Pawson

This figure shows the co-authorship network connecting the top 25 collaborators of Tony Pawson. A scholar is included among the top collaborators of Tony Pawson based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Tony Pawson. Tony Pawson is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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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.

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