Vincent DiGiacomo

562 total citations
15 papers, 405 citations indexed

About

Vincent DiGiacomo is a scholar working on Molecular Biology, Immunology and Allergy and Cellular and Molecular Neuroscience. According to data from OpenAlex, Vincent DiGiacomo has authored 15 papers receiving a total of 405 indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Molecular Biology, 4 papers in Immunology and Allergy and 3 papers in Cellular and Molecular Neuroscience. Recurrent topics in Vincent DiGiacomo's work include Protein Kinase Regulation and GTPase Signaling (9 papers), Receptor Mechanisms and Signaling (9 papers) and Cell Adhesion Molecules Research (4 papers). Vincent DiGiacomo is often cited by papers focused on Protein Kinase Regulation and GTPase Signaling (9 papers), Receptor Mechanisms and Signaling (9 papers) and Cell Adhesion Molecules Research (4 papers). Vincent DiGiacomo collaborates with scholars based in United States, Spain and United Kingdom. Vincent DiGiacomo's co-authors include Daniel Meruelo, Mikel Garcia‐Marcos, Arthur Marivin, Kshitij Parag‐Sharma, Anthony Leyme, Brandi Levin, Tomer Granot, Juan B. Blanco‐Canosa, Marcin Maziarz and Isabel Domínguez and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Journal of Biological Chemistry and Nature Communications.

In The Last Decade

Vincent DiGiacomo

15 papers receiving 401 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Vincent DiGiacomo United States 13 296 72 52 44 41 15 405
Samuel C. Griffiths United Kingdom 8 224 0.8× 57 0.8× 34 0.7× 43 1.0× 26 0.6× 14 330
Sabine Suppmann Germany 10 417 1.4× 52 0.7× 53 1.0× 34 0.8× 53 1.3× 15 636
Lee M. Wheldon United Kingdom 13 384 1.3× 84 1.2× 51 1.0× 27 0.6× 60 1.5× 19 467
Wen Qi Ho United States 5 396 1.3× 38 0.5× 18 0.3× 43 1.0× 19 0.5× 5 524
Sylvia A. Norman United States 10 243 0.8× 33 0.5× 70 1.3× 33 0.8× 49 1.2× 12 430
Verena Bachmann Germany 15 429 1.4× 99 1.4× 54 1.0× 116 2.6× 123 3.0× 17 686
Sean S Parghi United States 5 248 0.8× 97 1.3× 24 0.5× 58 1.3× 111 2.7× 7 433
Alan J. Situ United States 14 405 1.4× 33 0.5× 47 0.9× 24 0.5× 62 1.5× 20 488
Sonia Rodrigues Canada 8 219 0.7× 35 0.5× 34 0.7× 51 1.2× 70 1.7× 10 372
Marisa J. Wainszelbaum United States 12 238 0.8× 66 0.9× 15 0.3× 46 1.0× 46 1.1× 18 405

Countries citing papers authored by Vincent DiGiacomo

Since Specialization
Citations

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

Fields of papers citing papers by Vincent DiGiacomo

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Vincent DiGiacomo

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

All Works

15 of 15 papers shown
1.
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
2.
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
3.
DiGiacomo, Vincent, et al.. (2020). Mechanisms of aortic carboxypeptidase-like protein secretion and identification of an intracellularly retained variant associated with Ehlers–Danlos syndrome. Journal of Biological Chemistry. 295(28). 9725–9735. 13 indexed citations
4.
Marivin, Arthur, Marcin Maziarz, Jingyi Zhao, et al.. (2020). DAPLE protein inhibits nucleotide exchange on Gαs and Gαq via the same motif that activates Gαi. Journal of Biological Chemistry. 295(8). 2270–2284. 12 indexed citations
5.
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
6.
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
7.
DiGiacomo, Vincent, Alain Ibáñez de Opakua, Maria P. Papakonstantinou, et al.. (2017). The Gαi-GIV binding interface is a druggable protein-protein interaction. Scientific Reports. 7(1). 8575–8575. 19 indexed citations
8.
Opakua, Alain Ibáñez de, Kshitij Parag‐Sharma, Vincent DiGiacomo, et al.. (2017). Molecular mechanism of Gαi activation by non-GPCR proteins with a Gα-Binding and Activating motif. Nature Communications. 8(1). 15163–15163. 33 indexed citations
9.
Leyme, Anthony, Arthur Marivin, Marcin Maziarz, et al.. (2017). Specific inhibition of GPCR-independent G protein signaling by a rationally engineered protein. Proceedings of the National Academy of Sciences. 114(48). E10319–E10328. 18 indexed citations
10.
Parag‐Sharma, Kshitij, Anthony Leyme, Vincent DiGiacomo, et al.. (2016). Membrane Recruitment of the Non-receptor Protein GIV/Girdin (Gα-interacting, Vesicle-associated Protein/Girdin) Is Sufficient for Activating Heterotrimeric G Protein Signaling. Journal of Biological Chemistry. 291(53). 27098–27111. 19 indexed citations
11.
Marivin, Arthur, Anthony Leyme, Kshitij Parag‐Sharma, et al.. (2016). Dominant-negative Gα subunits are a mechanism of dysregulated heterotrimeric G protein signaling in human disease. Science Signaling. 9(423). ra37–ra37. 30 indexed citations
12.
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
13.
DiGiacomo, Vincent & Daniel Meruelo. (2015). Looking into laminin receptor: critical discussion regarding the non‐integrin 37/67‐kDalaminin receptor/RPSAprotein. Biological reviews/Biological reviews of the Cambridge Philosophical Society. 91(2). 288–310. 105 indexed citations
14.
DiGiacomo, Vincent, et al.. (2015). The transition of the 37-kDa laminin receptor (RPSA) to higher molecular weight species: SUMOylation or artifact?. Cellular & Molecular Biology Letters. 20(4). 571–85. 9 indexed citations
15.
Granot, Tomer, et al.. (2009). Enhanced specific delivery and targeting of oncolytic Sindbis viral vectors by modulating vascular leakiness in tumor. Cancer Gene Therapy. 17(4). 244–255. 50 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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