Mikel Garcia‐Marcos

7.1k total citations
77 papers, 2.4k citations indexed

About

Mikel Garcia‐Marcos is a scholar working on Molecular Biology, Cell Biology and Cellular and Molecular Neuroscience. According to data from OpenAlex, Mikel Garcia‐Marcos has authored 77 papers receiving a total of 2.4k indexed citations (citations by other indexed papers that have themselves been cited), including 63 papers in Molecular Biology, 17 papers in Cell Biology and 13 papers in Cellular and Molecular Neuroscience. Recurrent topics in Mikel Garcia‐Marcos's work include Protein Kinase Regulation and GTPase Signaling (34 papers), Receptor Mechanisms and Signaling (34 papers) and Cell Adhesion Molecules Research (11 papers). Mikel Garcia‐Marcos is often cited by papers focused on Protein Kinase Regulation and GTPase Signaling (34 papers), Receptor Mechanisms and Signaling (34 papers) and Cell Adhesion Molecules Research (11 papers). Mikel Garcia‐Marcos collaborates with scholars based in United States, Spain and Belgium. Mikel Garcia‐Marcos's co-authors include Pradipta Ghosh, Marilyn G. Farquhar, Jason Ear, Arthur Marivin, Anthony Leyme, Aída Marino, Jean‐Paul Dehaye, Scott J. Bornheimer, Marcin Maziarz and Stéphanie Pochet and has published in prestigious journals such as Cell, Proceedings of the National Academy of Sciences and Journal of Biological Chemistry.

In The Last Decade

Mikel Garcia‐Marcos

72 papers receiving 2.4k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Mikel Garcia‐Marcos United States 29 1.9k 458 290 255 249 77 2.4k
Jan Domin United Kingdom 29 1.6k 0.9× 904 2.0× 322 1.1× 124 0.5× 282 1.1× 43 2.6k
Reinhard Wetzker Germany 17 2.1k 1.1× 413 0.9× 339 1.2× 186 0.7× 397 1.6× 27 2.8k
José Vázquez‐Prado Mexico 27 1.9k 1.0× 550 1.2× 528 1.8× 158 0.6× 300 1.2× 69 2.5k
Thomas Eichholtz Netherlands 14 1.9k 1.0× 544 1.2× 178 0.6× 188 0.7× 187 0.8× 14 2.6k
Ben C. Tilly Netherlands 27 1.9k 1.0× 476 1.0× 412 1.4× 94 0.4× 351 1.4× 47 2.9k
Ingrid Verlaan Netherlands 19 2.2k 1.2× 616 1.3× 213 0.7× 191 0.7× 383 1.5× 25 2.8k
Kirsi Riento United Kingdom 18 2.1k 1.1× 1.3k 2.9× 265 0.9× 221 0.9× 310 1.2× 26 3.1k
Taroh Iiri Japan 30 2.1k 1.1× 354 0.8× 633 2.2× 109 0.4× 389 1.6× 72 3.2k
Yaowu Zheng China 18 1.6k 0.9× 297 0.6× 286 1.0× 134 0.5× 178 0.7× 47 3.4k
Thomas P. Stauffer Switzerland 11 1.7k 0.9× 847 1.8× 396 1.4× 160 0.6× 73 0.3× 17 2.2k

Countries citing papers authored by Mikel Garcia‐Marcos

Since Specialization
Citations

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

Fields of papers citing papers by Mikel Garcia‐Marcos

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Mikel Garcia‐Marcos. 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 Mikel Garcia‐Marcos. The network helps show where Mikel Garcia‐Marcos may publish in the future.

Co-authorship network of co-authors of Mikel Garcia‐Marcos

This figure shows the co-authorship network connecting the top 25 collaborators of Mikel Garcia‐Marcos. A scholar is included among the top collaborators of Mikel Garcia‐Marcos 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 Mikel Garcia‐Marcos. Mikel Garcia‐Marcos 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
1.
2.
Bischof, Felix, Angela Schulz, Susan Billig, et al.. (2025). Succinate receptor 1 signaling mutually depends on subcellular localization and cellular metabolism. FEBS Journal. 292(8). 2017–2050. 4 indexed citations
3.
Garcia‐Marcos, Mikel. (2024). Heterotrimeric G protein signaling without GPCRs: The Gα-binding-and-activating (GBA) motif. Journal of Biological Chemistry. 300(3). 105756–105756. 6 indexed citations
4.
5.
Maziarz, Marcin, Jong‐Chan Park, Jingyi Zhao, et al.. (2024). Direct interrogation of context-dependent GPCR activity with a universal biosensor platform. Cell. 187(6). 1527–1546.e25. 23 indexed citations
6.
Zhao, Jingyi, Vincent DiGiacomo, Shiva Dastjerdi, et al.. (2023). Small-molecule targeting of GPCR-independent noncanonical G-protein signaling in cancer. Proceedings of the National Academy of Sciences. 120(18). 8 indexed citations
7.
Marivin, Arthur, Rachel Ho, & Mikel Garcia‐Marcos. (2022). DAPLE orchestrates apical actomyosin assembly from junctional polarity complexes. The Journal of Cell Biology. 221(5). 4 indexed citations
8.
DiGiacomo, Vincent, et al.. (2020). Probing the mutational landscape of regulators of G protein signaling proteins in cancer. Science Signaling. 13(617). 18 indexed citations
9.
Kalogriopoulos, Nicholas A., Inmaculada López-Sánchez, Chang‐Shen Lin, et al.. (2020). Receptor tyrosine kinases activate heterotrimeric G proteins via phosphorylation within the interdomain cleft of Gαi. Proceedings of the National Academy of Sciences. 117(46). 28763–28774. 22 indexed citations
10.
Maziarz, Marcin, et al.. (2020). Revealing the Activity of Trimeric G-proteins in Live Cells with a Versatile Biosensor Design. Cell. 182(3). 770–785.e16. 71 indexed citations
11.
Marivin, Arthur, Anthony Leyme, Dmitry A. Kretov, et al.. (2019). GPCR-independent activation of G proteins promotes apical cell constriction in vivo. The Journal of Cell Biology. 218(5). 1743–1763. 17 indexed citations
12.
Maziarz, Marcin, Stefan Broselid, Vincent DiGiacomo, et al.. (2018). A biochemical and genetic discovery pipeline identifies PLCδ4b as a nonreceptor activator of heterotrimeric G-proteins. Journal of Biological Chemistry. 293(44). 16964–16983. 17 indexed citations
13.
DiGiacomo, Vincent, Arthur Marivin, & Mikel Garcia‐Marcos. (2017). When Heterotrimeric G Proteins Are Not Activated by G Protein-Coupled Receptors: Structural Insights and Evolutionary Conservation. Biochemistry. 57(3). 255–257. 25 indexed citations
14.
Marivin, Arthur, Kshitij Parag‐Sharma, Vincent DiGiacomo, et al.. (2015). Evolutionary Conservation of a GPCR-Independent Mechanism of Trimeric G Protein Activation. Molecular Biology and Evolution. 33(3). 820–837. 29 indexed citations
15.
Colvin, Teresa A., Vladimir L. Gabai, Jianlin Gong, et al.. (2014). Hsp70–Bag3 Interactions Regulate Cancer-Related Signaling Networks. Cancer Research. 74(17). 4731–4740. 137 indexed citations
16.
Lin, Chang‐Shen, Jason Ear, Krishna Midde, et al.. (2014). Structural basis for activation of trimeric Gi proteins by multiple growth factor receptors via GIV/Girdin. Molecular Biology of the Cell. 25(22). 3654–3671. 47 indexed citations
17.
López-Sánchez, Inmaculada, Mikel Garcia‐Marcos, Yash Mittal, et al.. (2013). Protein kinase C-theta (PKCθ) phosphorylates and inhibits the guanine exchange factor, GIV/Girdin. Proceedings of the National Academy of Sciences. 110(14). 5510–5515. 33 indexed citations
18.
Ghosh, Pradipta, Mikel Garcia‐Marcos, & Marilyn G. Farquhar. (2011). GIV/Girdin is a rheostat that fine-tunes growth factor signals during tumor progression. Cell Adhesion & Migration. 5(3). 237–248. 48 indexed citations
19.
Pochet, Stéphanie, et al.. (2007). Contribution of two ionotropic purinergic receptors to ATP responses in submandibular gland ductal cells. Cellular Signalling. 19(10). 2155–2164. 21 indexed citations
20.
Pochet, Stéphanie, et al.. (2003). Regulation by clozapine of calcium handling by rat submandibular acinar cells. Cell Calcium. 34(6). 465–475. 9 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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