Gavin MacBeath

11.6k total citations · 4 hit papers
83 papers, 8.0k citations indexed

About

Gavin MacBeath is a scholar working on Molecular Biology, Oncology and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, Gavin MacBeath has authored 83 papers receiving a total of 8.0k indexed citations (citations by other indexed papers that have themselves been cited), including 53 papers in Molecular Biology, 32 papers in Oncology and 25 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in Gavin MacBeath's work include Monoclonal and Polyclonal Antibodies Research (25 papers), HER2/EGFR in Cancer Research (24 papers) and Advanced Biosensing Techniques and Applications (24 papers). Gavin MacBeath is often cited by papers focused on Monoclonal and Polyclonal Antibodies Research (25 papers), HER2/EGFR in Cancer Research (24 papers) and Advanced Biosensing Techniques and Applications (24 papers). Gavin MacBeath collaborates with scholars based in United States, Germany and Canada. Gavin MacBeath's co-authors include Stuart L. Schreiber, Andrew Gordus, Peter K. Sorger, Jordan A. Krall, Richard B. Jones, Donald Hilvert, Taranjit S. Gujral, Angela N. Koehler, Mark Sevecka and Peter Kast and has published in prestigious journals such as Nature, Science and Cell.

In The Last Decade

Gavin MacBeath

81 papers receiving 7.8k citations

Hit Papers

align trajectories

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 threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Printing Proteins as Microarrays for High-Throughput Function Determination

2000 2.3k citations Gavin MacBeath et al. profile →
Protein microarrays and proteomics

2002 644 citations Gavin MacBeath profile →
A quantitative protein interaction network for the ErbB receptors using protein microarrays

2005 569 citations Richard B. Jones, Andrew Gordus et al. Nature profile →
Sequential Application of Anticancer Drugs Enhances Cell Death by Rewiring Apoptotic Signaling Networks

2012 528 citations Peter K. Sorger, Gavin MacBeath et al. Cell profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Gavin MacBeath United States	34	6.2k	2.0k	1.7k	978	683	83	8.0k
Rebecca L. Rich United States	44	5.1k 0.8×	1.2k 0.6×	950 0.5×	843 0.9×	251 0.4×	71	7.8k
David G. Myszka United States	62	9.1k 1.5×	2.9k 1.4×	1.7k 1.0×	938 1.0×	430 0.6×	133	13.2k
Robert Karlsson Sweden	31	4.2k 0.7×	2.3k 1.1×	1.1k 0.7×	325 0.3×	273 0.4×	65	6.1k
Juri G. Gelovani United States	59	5.1k 0.8×	2.3k 1.1×	2.2k 1.3×	2.3k 2.3×	286 0.4×	247	11.3k
Emanuel F. Petricoin United States	51	6.7k 1.1×	1.4k 0.7×	945 0.5×	1.5k 1.5×	2.3k 3.3×	195	9.5k
Virginia Espina United States	49	5.0k 0.8×	1.2k 0.6×	871 0.5×	1.3k 1.3×	1.5k 2.2×	152	7.3k
Julia Wulfkuhle United States	36	4.1k 0.7×	918 0.4×	778 0.4×	1.2k 1.2×	1.2k 1.8×	81	5.8k
Philippe I. H. Bastiaens Germany	56	8.5k 1.4×	746 0.4×	808 0.5×	1.3k 1.4×	316 0.5×	138	11.3k
Jason W. Chin United Kingdom	73	15.5k 2.5×	2.4k 1.2×	511 0.3×	1.6k 1.6×	428 0.6×	156	18.2k
Derek N. Woolfson United Kingdom	65	10.1k 1.6×	746 0.4×	741 0.4×	376 0.4×	619 0.9×	214	13.3k

Countries citing papers authored by Gavin MacBeath

Since Specialization

Citations

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

Fields of papers citing papers by Gavin MacBeath

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Gavin MacBeath. 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 Gavin MacBeath. The network helps show where Gavin MacBeath may publish in the future.

Co-authorship network of co-authors of Gavin MacBeath

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

All Works

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20 of 20 papers shown

Malki, Monzr M. Al, Alla Keyzner, Hyung C. Suh, et al.. (2024). A phase 1 trial of TSC-100 and TSC-101, engineered T cell therapies that target minor histocompatibility antigens to eliminate residual disease after hematopoietic cell transplantation.. Journal of Clinical Oncology. 42(16_suppl). TPS2678–TPS2678. 1 indexed citations

Thomas, Sajeve, Brian S. Henick, Rom S. Leidner, et al.. (2024). Initial data from a phase 1, first-in-human clinical trial for T-Plex, a multiplexed, enhanced T cell receptor-engineered T cell therapy (TCR-T) for solid tumors.. Journal of Clinical Oncology. 42(16_suppl). 2542–2542.

Ferretti, Andrew, Tomasz Kula, Yifan Wang, et al.. (2020). Unbiased Screens Show CD8+ T Cells of COVID-19 Patients Recognize Shared Epitopes in SARS-CoV-2 that Largely Reside outside the Spike Protein. Immunity. 53(5). 1095–1107.e3. 182 indexed citations

Sabnis, Gauri, Bambang S. Adiwijaya, Gabriela Garcia, et al.. (2015). Seribantumab, an Anti-ERBB3 Antibody, Delays the Onset of Resistance and Restores Sensitivity to Letrozole in an Estrogen Receptor–Positive Breast Cancer Model. Molecular Cancer Therapeutics. 14(11). 2642–2652. 19 indexed citations

Yarar, Defne, Johanna Lahdenranta, William Kubasek, Ulrik B. Nielsen, & Gavin MacBeath. (2015). Heregulin–ErbB3-Driven Tumor Growth Persists in PI3 Kinase Mutant Cancer Cells. Molecular Cancer Therapeutics. 14(9). 2072–2080. 4 indexed citations

Qian, Guoqing, Ning Jiang, Dongsheng Wang, et al.. (2015). Heregulin and HER3 are prognostic biomarkers in oropharyngeal squamous cell carcinoma. Cancer. 121(20). 3600–3611. 33 indexed citations

Jiang, Ning, Dongsheng Wang, Zhongliang Hu, et al.. (2014). Combination of Anti-HER3 Antibody MM-121/SAR256212 and Cetuximab Inhibits Tumor Growth in Preclinical Models of Head and Neck Squamous Cell Carcinoma. Molecular Cancer Therapeutics. 13(7). 1826–1836. 50 indexed citations

Gujral, Taranjit S., Marina Chan, Leonid Peshkin, et al.. (2014). A Noncanonical Frizzled2 Pathway Regulates Epithelial-Mesenchymal Transition and Metastasis. Cell. 159(4). 844–856. 271 indexed citations

Allen, John E., Brian C. Russo, Soo Young Lee, et al.. (2014). Systematic Analysis of Bacterial Effector-Postsynaptic Density 95/Disc Large/Zonula Occludens-1 (PDZ) Domain Interactions Demonstrates Shigella OspE Protein Promotes Protein Kinase C Activation via PDLIM Proteins. Journal of Biological Chemistry. 289(43). 30101–30113. 14 indexed citations

10.

Onsum, Matthew, Elena Geretti, Violette Paragas, et al.. (2013). Single-Cell Quantitative HER2 Measurement Identifies Heterogeneity and Distinct Subgroups within Traditionally Defined HER2-Positive Patients. American Journal Of Pathology. 183(5). 1446–1460. 72 indexed citations

11.

Kaushansky, Alexis, et al.. (2013). Phosphotyrosine Signaling Proteins that Drive Oncogenesis Tend to be Highly Interconnected. Molecular & Cellular Proteomics. 12(5). 1204–1213. 28 indexed citations

12.

Gujral, Taranjit S., et al.. (2013). Family-wide Investigation of PDZ Domain-Mediated Protein-Protein Interactions Implicates β-Catenin in Maintaining the Integrity of Tight Junctions. Chemistry & Biology. 20(6). 816–827. 27 indexed citations

13.

MacBeath, Gavin, et al.. (2012). Cross-talk between Receptor Tyrosine Kinase and Tumor Necrosis Factor-α Signaling Networks Regulates Apoptosis but not Proliferation. Molecular & Cellular Proteomics. 11(6). M111.013292–M111.013292. 19 indexed citations

14.

Gujral, Taranjit S., Robert L. Karp, David W. Chan, et al.. (2012). Profiling phospho-signaling networks in breast cancer using reverse-phase protein arrays. Oncogene. 32(29). 3470–3476. 62 indexed citations

15.

Krall, Jordan A., et al.. (2011). High- and Low-Affinity Epidermal Growth Factor Receptor-Ligand Interactions Activate Distinct Signaling Pathways. PLoS ONE. 6(1). e15945–e15945. 83 indexed citations

16.

Shalek, Alex K., Jacob T. Robinson, Ethan S. Karp, et al.. (2010). Vertical silicon nanowires as a universal platform for delivering biomolecules into living cells. Proceedings of the National Academy of Sciences. 107(5). 1870–1875. 466 indexed citations

17.

Kaushansky, Alexis, et al.. (2008). A quantitative study of the recruitment potential of all intracellulartyrosine residues on EGFR, FGFR1 and IGF1R. Molecular BioSystems. 4(6). 643–653. 44 indexed citations

18.

Kaushansky, Alexis, Andrew Gordus, Bogdan Budnik, et al.. (2008). System-wide Investigation of ErbB4 Reveals 19 Sites of Tyr Phosphorylation that Are Unusually Selective in Their Recruitment Properties. Chemistry & Biology. 15(8). 808–817. 64 indexed citations

19.

Jones, Richard B., Andrew Gordus, Jordan A. Krall, & Gavin MacBeath. (2005). A quantitative protein interaction network for the ErbB receptors using protein microarrays. Nature. 439(7073). 168–174. 569 indexed citations breakdown →

20.

Nielsen, Ulrik B., et al.. (2003). Profiling receptor tyrosine kinase activation by using Ab microarrays. Proceedings of the National Academy of Sciences. 100(16). 9330–9335. 179 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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