John Barkinge

631 total citations
9 papers, 515 citations indexed

About

John Barkinge is a scholar working on Molecular Biology, Radiology, Nuclear Medicine and Imaging and Pulmonary and Respiratory Medicine. According to data from OpenAlex, John Barkinge has authored 9 papers receiving a total of 515 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Molecular Biology, 3 papers in Radiology, Nuclear Medicine and Imaging and 2 papers in Pulmonary and Respiratory Medicine. Recurrent topics in John Barkinge's work include Cell death mechanisms and regulation (4 papers), Monoclonal and Polyclonal Antibodies Research (3 papers) and Cancer therapeutics and mechanisms (1 paper). John Barkinge is often cited by papers focused on Cell death mechanisms and regulation (4 papers), Monoclonal and Polyclonal Antibodies Research (3 papers) and Cancer therapeutics and mechanisms (1 paper). John Barkinge collaborates with scholars based in United States, Austria and United Kingdom. John Barkinge's co-authors include Radhika Gudi, Fei Chu, Prasad Kanteti, Ravi Salgia, Richard B. Jones, Mark F. Ciaccio, Chih‐Pin Chuu, Giulio Superti‐Furga, Akiko Koide and John Wojcik and has published in prestigious journals such as PLoS ONE, Cancer Research and Oncogene.

In The Last Decade

John Barkinge

9 papers receiving 504 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
John Barkinge United States	9	328	203	129	61	57	9	515
Alexander Kurtenbach Germany	5	401 1.2×	133 0.7×	76 0.6×	28 0.5×	46 0.8×	5	664
Sarai Rodríguez Spain	9	381 1.2×	205 1.0×	54 0.4×	93 1.5×	105 1.8×	11	654
Heike I. Krupka United States	11	332 1.0×	212 1.0×	112 0.9×	91 1.5×	30 0.5×	15	608
Corinne Venot France	12	528 1.6×	404 2.0×	84 0.7×	36 0.6×	36 0.6×	17	751
Indranil Basu United States	9	344 1.0×	158 0.8×	42 0.3×	24 0.4×	50 0.9×	17	543
Cory L. Painter United States	10	278 0.8×	190 0.9×	66 0.5×	29 0.5×	83 1.5×	15	470
Christoph Rösli Switzerland	8	245 0.7×	137 0.7×	168 1.3×	22 0.4×	29 0.5×	10	487
Chris Herring United Kingdom	4	428 1.3×	95 0.5×	228 1.8×	37 0.6×	16 0.3×	5	594
Cheng‐Pang Hsu United States	9	396 1.2×	197 1.0×	99 0.8×	37 0.6×	30 0.5×	9	574
M. K. White United States	13	311 0.9×	209 1.0×	34 0.3×	50 0.8×	27 0.5×	18	577

Countries citing papers authored by John Barkinge

Since Specialization

Citations

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

Fields of papers citing papers by John Barkinge

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of John Barkinge

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

All Works

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9 of 9 papers shown

Hause, Ronald J., et al.. (2014). Enhanced Prediction of Src Homology 2 (SH2) Domain Binding Potentials Using a Fluorescence Polarization-derived c-Met, c-Kit, ErbB, and Androgen Receptor Interactome. Molecular & Cellular Proteomics. 13(7). 1705–1723. 16 indexed citations

Hause, Ronald J., et al.. (2012). Comprehensive Binary Interaction Mapping of SH2 Domains via Fluorescence Polarization Reveals Novel Functional Diversification of ErbB Receptors. PLoS ONE. 7(9). e44471–e44471. 49 indexed citations

Wojcik, John, Oliver Hantschel, Florian Grebien, et al.. (2010). A potent and highly specific FN3 monobody inhibitor of the Abl SH2 domain. Nature Structural & Molecular Biology. 17(4). 519–527. 128 indexed citations

Prasad, K. S. Srinivasa, John Barkinge, Radhika Gudi, et al.. (2009). The p53-induced Siva-1 plays a significant role in cisplatin-mediated apoptosis. Journal of Carcinogenesis. 8(1). 2–2. 15 indexed citations

Gudi, Radhika, et al.. (2009). Siva-1 Promotes K-48 Polyubiquitination of TRAF2 and Inhibits TCR-Mediated Activation of NF-kappaB. Journal of Environmental Pathology Toxicology and Oncology. 28(1). 25–38. 16 indexed citations

Chuu, Chih‐Pin, et al.. (2008). Systems-Level Analysis of ErbB4 Signaling in Breast Cancer: A Laboratory to Clinical Perspective. Molecular Cancer Research. 6(6). 885–891. 24 indexed citations

Gudi, Radhika, John Barkinge, Fei Chu, et al.. (2006). Siva-1 negatively regulates NF-κB activity: effect on T-cell receptor-mediated activation-induced cell death (AICD). Oncogene. 25(24). 3458–3462. 30 indexed citations

Chu, Fei, et al.. (2005). Expression of Siva-1 Protein or Its Putative Amphipathic Helical Region Enhances Cisplatin-Induced Apoptosis in Breast Cancer Cells: Effect of Elevated Levels of BCL-2. Cancer Research. 65(12). 5301–5309. 198 indexed citations

Chu, Fei, Alip Borthakur, Xi Sun, et al.. (2004). The Siva-1 putative amphipathic helical region (SAH) is sufficient to bind to BCL-XL and sensitize cells to UV radiation induced apoptosis. APOPTOSIS. 9(1). 83–95. 39 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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