Kebing Yu

2.5k total citations
38 papers, 1.5k citations indexed

About

Kebing Yu is a scholar working on Molecular Biology, Immunology and Spectroscopy. According to data from OpenAlex, Kebing Yu has authored 38 papers receiving a total of 1.5k indexed citations (citations by other indexed papers that have themselves been cited), including 33 papers in Molecular Biology, 8 papers in Immunology and 7 papers in Spectroscopy. Recurrent topics in Kebing Yu's work include Ubiquitin and proteasome pathways (8 papers), Advanced Proteomics Techniques and Applications (7 papers) and Protein Kinase Regulation and GTPase Signaling (5 papers). Kebing Yu is often cited by papers focused on Ubiquitin and proteasome pathways (8 papers), Advanced Proteomics Techniques and Applications (7 papers) and Protein Kinase Regulation and GTPase Signaling (5 papers). Kebing Yu collaborates with scholars based in United States, France and Singapore. Kebing Yu's co-authors include Arthur R. Salomon, Maik Hüttemann, Icksoo Lee, Donald S. Kirkpatrick, P. Taylur, Lulu Cao, Kim Newton, Steffan Vartanian, Domagoj Vucic and Hong Yu and has published in prestigious journals such as Nature, Cell and Journal of the American Chemical Society.

In The Last Decade

Kebing Yu

38 papers receiving 1.4k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Kebing Yu United States 21 1.1k 354 168 161 144 38 1.5k
Severine Gharbi Spain 16 919 0.8× 200 0.6× 174 1.0× 232 1.4× 89 0.6× 21 1.3k
Karim Rezaul United States 15 1.1k 1.0× 354 1.0× 165 1.0× 290 1.8× 117 0.8× 22 1.5k
Jintang He United States 22 800 0.7× 178 0.5× 355 2.1× 285 1.8× 131 0.9× 40 1.3k
Punit Saraon Canada 19 805 0.7× 152 0.4× 236 1.4× 122 0.8× 267 1.9× 25 1.5k
Jeong Heon Ko South Korea 20 1.2k 1.1× 589 1.7× 371 2.2× 125 0.8× 171 1.2× 41 1.6k
Sarah Hanrahan United Kingdom 17 1.2k 1.1× 205 0.6× 234 1.4× 122 0.8× 370 2.6× 24 1.8k
Takuro Ariga Japan 20 770 0.7× 229 0.6× 96 0.6× 74 0.5× 83 0.6× 88 1.6k
Eric S. Witze United States 17 1.4k 1.2× 125 0.4× 277 1.6× 311 1.9× 168 1.2× 25 1.8k
Urs Lewandrowski Germany 23 1.0k 0.9× 142 0.4× 113 0.7× 474 2.9× 155 1.1× 35 1.8k
Andrew Pierce United Kingdom 23 1.3k 1.2× 254 0.7× 423 2.5× 230 1.4× 270 1.9× 69 2.2k

Countries citing papers authored by Kebing Yu

Since Specialization
Citations

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

Fields of papers citing papers by Kebing Yu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Kebing Yu

This figure shows the co-authorship network connecting the top 25 collaborators of Kebing Yu. A scholar is included among the top collaborators of Kebing Yu 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 Kebing Yu. Kebing Yu 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.
Amara, Neri, Maria A. Voronkova, Bradley A. Webb, et al.. (2021). Selective activation of PFKL suppresses the phagocytic oxidative burst. Cell. 184(17). 4480–4494.e15. 105 indexed citations
2.
Cho, Kelvin F., P. Taylur, Christopher M. Rose, et al.. (2020). Chaperone mediated detection of small molecule target binding in cells. Nature Communications. 11(1). 465–465. 10 indexed citations
3.
Pham, Victoria C., Joshua D. Webster, Rohit Reja, et al.. (2019). The RIPK4–IRF6 signalling axis safeguards epidermal differentiation and barrier function. Nature. 574(7777). 249–253. 54 indexed citations
4.
Hewings, David S., Johanna Heideker, P. Taylur, et al.. (2018). Reactive-site-centric chemoproteomics identifies a distinct class of deubiquitinase enzymes. Nature Communications. 9(1). 1162–1162. 71 indexed citations
5.
Goncharov, Tatiana, Melinda M. Mulvihill, Anita Izrael-Tomasevic, et al.. (2018). Disruption of XIAP-RIP2 Association Blocks NOD2-Mediated Inflammatory Signaling. Molecular Cell. 69(4). 551–565.e7. 86 indexed citations
6.
Almagro, M. Cristina de, Tatiana Goncharov, Anita Izrael-Tomasevic, et al.. (2016). Coordinated ubiquitination and phosphorylation of RIP1 regulates necroptotic cell death. Cell Death and Differentiation. 24(1). 26–37. 95 indexed citations
7.
Anania, Veronica G., Kebing Yu, Florian Gnad, et al.. (2016). Uncovering a Dual Regulatory Role for Caspases During Endoplasmic Reticulum Stress-induced Cell Death. Molecular & Cellular Proteomics. 15(7). 2293–2307. 7 indexed citations
8.
West, Mark J., et al.. (2014). Novel Cul3 binding proteins function to remodel E3 ligase complexes. BMC Cell Biology. 15(1). 28–28. 10 indexed citations
9.
Sanderson, Thomas H., Gargi Mahapatra, Petr Pecina, et al.. (2013). Cytochrome c Is Tyrosine 97 Phosphorylated by Neuroprotective Insulin Treatment. PLoS ONE. 8(11). e78627–e78627. 50 indexed citations
10.
Cao, Lulu, et al.. (2012). Quantitative Phosphoproteomics Reveals SLP-76 Dependent Regulation of PAG and Src Family Kinases in T Cells. PLoS ONE. 7(10). e46725–e46725. 19 indexed citations
11.
O’Brien, Xian M., Liz M. Lavigne, Kebing Yu, et al.. (2011). Lectin Site Ligation of CR3 Induces Conformational Changes and Signaling. Journal of Biological Chemistry. 287(5). 3337–3348. 56 indexed citations
12.
Agrawal, Pooja, Kebing Yu, Arthur R. Salomon, & John M. Sedivy. (2010). Proteomic profiling of Myc-associated proteins . Cell Cycle. 9(24). 4908–4921. 52 indexed citations
13.
Yu, Kebing & Arthur R. Salomon. (2010). HTAPP: High‐throughput autonomous proteomic pipeline. PROTEOMICS. 10(11). 2113–2122. 32 indexed citations
14.
Lee, Icksoo, Arthur R. Salomon, Kebing Yu, et al.. (2009). Chapter 11 Isolation of Regulatory‐Competent, Phosphorylated Cytochrome c Oxidase. Methods in enzymology on CD-ROM/Methods in enzymology. 457. 193–210. 38 indexed citations
15.
Yu, Kebing & Arthur R. Salomon. (2009). PeptideDepot: Flexible relational database for visual analysis of quantitative proteomic data and integration of existing protein information. PROTEOMICS. 9(23). 5350–5358. 34 indexed citations
16.
Nguyen, Vinh T., Lulu Cao, Anna Ritz, et al.. (2009). A New Approach for Quantitative Phosphoproteomic Dissection of Signaling Pathways Applied to T Cell Receptor Activation. Molecular & Cellular Proteomics. 8(11). 2418–2431. 67 indexed citations
17.
Yu, Kebing, et al.. (2009). Integrated platform for manual and high‐throughput statistical validation of tandem mass spectra. PROTEOMICS. 9(11). 3115–3125. 29 indexed citations
18.
Jianu, Radu, Kebing Yu, Lulu Cao, et al.. (2009). Visual Integration of Quantitative Proteomic Data, Pathways, and Protein Interactions. IEEE Transactions on Visualization and Computer Graphics. 16(4). 609–620. 11 indexed citations
19.
Cao, Lulu, Kebing Yu, Vinh T. Nguyen, et al.. (2007). Quantitative Time-Resolved Phosphoproteomic Analysis of Mast Cell Signaling. The Journal of Immunology. 179(9). 5864–5876. 63 indexed citations
20.
Cao, Lulu, Kebing Yu, & Arthur R. Salomon. (2007). Phosphoproteomic Analysis of Lymphocyte Signaling. Advances in experimental medicine and biology. 584. 277–288. 4 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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