George M. Burslem

4.3k total citations · 3 hit papers
54 papers, 3.2k citations indexed

About

George M. Burslem is a scholar working on Molecular Biology, Organic Chemistry and Oncology. According to data from OpenAlex, George M. Burslem has authored 54 papers receiving a total of 3.2k indexed citations (citations by other indexed papers that have themselves been cited), including 43 papers in Molecular Biology, 14 papers in Organic Chemistry and 10 papers in Oncology. Recurrent topics in George M. Burslem's work include Protein Degradation and Inhibitors (18 papers), Ubiquitin and proteasome pathways (13 papers) and Click Chemistry and Applications (11 papers). George M. Burslem is often cited by papers focused on Protein Degradation and Inhibitors (18 papers), Ubiquitin and proteasome pathways (13 papers) and Click Chemistry and Applications (11 papers). George M. Burslem collaborates with scholars based in United States, United Kingdom and France. George M. Burslem's co-authors include Craig M. Crews, Daniel P. Bondeson, John Hines, Saul Jaime‐Figueroa, Blake E. Smith, Jing Wang, Brian D. Hamman, Alexandru D. Buhimschi, Alexey Ishchenko and Andrew J. Wilson and has published in prestigious journals such as Science, Cell and Chemical Reviews.

In The Last Decade

George M. Burslem

48 papers receiving 3.1k citations

Hit Papers

Proteolysis-Targeting Chi... 2017 2026 2020 2023 2020 2017 2017 200 400 600

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
George M. Burslem United States 20 2.8k 1.1k 699 425 128 54 3.2k
Andrew P. Crew United States 21 3.1k 1.1× 1.2k 1.1× 967 1.4× 357 0.8× 66 0.5× 37 3.5k
John Hines United States 24 4.1k 1.5× 1.7k 1.6× 1.2k 1.7× 343 0.8× 82 0.6× 42 4.6k
Kanak Raina United States 14 2.8k 1.0× 996 0.9× 828 1.2× 166 0.4× 65 0.5× 23 3.0k
Saul Jaime‐Figueroa United States 20 2.7k 1.0× 1.2k 1.1× 814 1.2× 480 1.1× 63 0.5× 27 3.2k
Taavi K. Neklesa United States 18 2.0k 0.7× 784 0.7× 380 0.5× 141 0.3× 65 0.5× 25 2.2k
Frank Boschelli United States 28 1.4k 0.5× 581 0.5× 823 1.2× 654 1.5× 70 0.5× 69 2.6k
Stephen K. Tahir United States 22 2.4k 0.9× 980 0.9× 337 0.5× 331 0.8× 86 0.7× 35 3.3k
William C. Shakespeare United States 29 1.8k 0.6× 933 0.8× 666 1.0× 816 1.9× 187 1.5× 59 3.2k
Alexander R. Shoemaker United States 19 2.2k 0.8× 906 0.8× 233 0.3× 332 0.8× 79 0.6× 22 3.0k
Pingda Ren United States 21 2.3k 0.8× 570 0.5× 248 0.4× 636 1.5× 93 0.7× 49 3.2k

Countries citing papers authored by George M. Burslem

Since Specialization
Citations

This map shows the geographic impact of George M. Burslem'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 George M. Burslem with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites George M. Burslem more than expected).

Fields of papers citing papers by George M. Burslem

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by George M. Burslem. 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 George M. Burslem. The network helps show where George M. Burslem may publish in the future.

Co-authorship network of co-authors of George M. Burslem

This figure shows the co-authorship network connecting the top 25 collaborators of George M. Burslem. A scholar is included among the top collaborators of George M. Burslem 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 George M. Burslem. George M. Burslem is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
2.
Burslem, George M., et al.. (2025). Acetylation: a new target for protein degradation in cancer. Trends in cancer. 11(4). 403–420. 1 indexed citations
4.
Hintzen, Jordi C. J., Mohd Altaf Najar, Takeshi Tsusaka, et al.. (2025). Class I histone deacetylases catalyze lysine lactylation. Journal of Biological Chemistry. 301(10). 110602–110602. 3 indexed citations
5.
Serebrenik, Yevgeniy V., et al.. (2025). Pooled tagging and hydrophobic targeting of endogenous proteins for unbiased mapping of unfolded protein responses. Molecular Cell. 85(9). 1868–1886.e12. 2 indexed citations
6.
Noël, M., et al.. (2024). Sortase mediated protein ubiquitination with defined chain length and topology. RSC Chemical Biology. 5(4). 321–327. 2 indexed citations
7.
Chan, Alexander, Rebecca M. Haley, Mohd Altaf Najar, et al.. (2024). Lipid-mediated intracellular delivery of recombinant bioPROTACs for the rapid degradation of undruggable proteins. Nature Communications. 15(1). 5808–5808. 28 indexed citations
8.
Papadaki, Georgia, et al.. (2023). A Chicken Tapasin ortholog can chaperone empty HLA-B∗37:01 molecules independent of other peptide-loading components. Journal of Biological Chemistry. 299(10). 105136–105136. 2 indexed citations
9.
Sun, Yi, et al.. (2023). Universal open MHC-I molecules for rapid peptide loading and enhanced complex stability across HLA allotypes. Proceedings of the National Academy of Sciences. 120(25). e2304055120–e2304055120. 13 indexed citations
10.
Sun, Yi, et al.. (2023). Xeno interactions between MHC-I proteins and molecular chaperones enable ligand exchange on a broad repertoire of HLA allotypes. Science Advances. 9(8). eade7151–eade7151. 10 indexed citations
11.
Ren, Jian‐Gang, Bowen Xing, Kaosheng Lv, et al.. (2023). RAB27B controls palmitoylation-dependent NRAS trafficking and signaling in myeloid leukemia. Journal of Clinical Investigation. 133(12). 24 indexed citations
12.
Xu, Kexiang, Swarbhanu Sarkar, Tommy Nguyen, et al.. (2023). Regulation of eDHFR-tagged proteins with trimethoprim PROTACs. Nature Communications. 14(1). 7071–7071. 8 indexed citations
13.
Grasso, Michael, Ye‐Jin Kim, Stefanie D. Boyd, et al.. (2021). The copper chaperone CCS facilitates copper binding to MEK1/2 to promote kinase activation. Journal of Biological Chemistry. 297(6). 101314–101314. 60 indexed citations
14.
Burslem, George M., et al.. (2021). Focused Libraries for Epigenetic Drug Discovery: The Importance of Isosteres. Journal of Medicinal Chemistry. 64(11). 7231–7240. 17 indexed citations
15.
Burslem, George M., Daniel P. Bondeson, & Craig M. Crews. (2020). Scaffold hopping enables direct access to more potent PROTACs with in vivo activity. Chemical Communications. 56(50). 6890–6892. 30 indexed citations
16.
Burslem, George M., Anna Reister Schultz, Daniel P. Bondeson, et al.. (2019). Targeting BCR-ABL1 in Chronic Myeloid Leukemia by PROTAC-Mediated Targeted Protein Degradation. Cancer Research. 79(18). 4744–4753. 165 indexed citations
17.
Grison, Claire M., George M. Burslem, Jennifer A. Miles, et al.. (2017). Double quick, double click reversible peptide “stapling”. Chemical Science. 8(7). 5166–5171. 82 indexed citations
18.
Burslem, George M., Hannah F. Kyle, Adam Nelson, Thomas A. Edwards, & Andrew J. Wilson. (2017). Hypoxia inducible factor (HIF) as a model for studying inhibition of protein–protein interactions. Chemical Science. 8(6). 4188–4202. 31 indexed citations
19.
Burslem, George M. & Craig M. Crews. (2017). Small-Molecule Modulation of Protein Homeostasis. Chemical Reviews. 117(17). 11269–11301. 220 indexed citations
20.
Burslem, George M., Hannah F. Kyle, Alexander L. Breeze, et al.. (2014). Small‐Molecule Proteomimetic Inhibitors of the HIF‐1α–p300 Protein–Protein Interaction. ChemBioChem. 15(8). 1083–1087. 60 indexed citations

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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