Sukhdeep K. Spall

2.6k total citations · 2 hit papers
12 papers, 1.4k citations indexed

About

Sukhdeep K. Spall is a scholar working on Molecular Biology, Immunology and Genetics. According to data from OpenAlex, Sukhdeep K. Spall has authored 12 papers receiving a total of 1.4k indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Molecular Biology, 5 papers in Immunology and 4 papers in Genetics. Recurrent topics in Sukhdeep K. Spall's work include Bacterial Genetics and Biotechnology (4 papers), Cell death mechanisms and regulation (3 papers) and Phagocytosis and Immune Regulation (3 papers). Sukhdeep K. Spall is often cited by papers focused on Bacterial Genetics and Biotechnology (4 papers), Cell death mechanisms and regulation (3 papers) and Phagocytosis and Immune Regulation (3 papers). Sukhdeep K. Spall collaborates with scholars based in Australia, Switzerland and United States. Sukhdeep K. Spall's co-authors include John Silke, Warren S. Alexander, W. Wei‐Lynn Wong, Holly Anderton, Andrew I. Webb, Cathrine Hall, David L. Vaux, Maria C. Tanzer, Kaye N. Truscott and David A. Dougan and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Nature Communications and The EMBO Journal.

In The Last Decade

Sukhdeep K. Spall

11 papers receiving 1.4k citations

Hit Papers

RIPK3 promotes cell death and NLRP3 inflammasome activati... 2014 2026 2018 2022 2015 2014 100 200 300 400 500

Peers

Sukhdeep K. Spall
Jingping Shen United States
Fay J. Dufort United States
Ge Shi China
Lawrence H. Cheung United States
Jingping Shen United States
Sukhdeep K. Spall
Citations per year, relative to Sukhdeep K. Spall Sukhdeep K. Spall (= 1×) peers Jingping Shen

Countries citing papers authored by Sukhdeep K. Spall

Since Specialization
Citations

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

Fields of papers citing papers by Sukhdeep K. Spall

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Sukhdeep K. Spall. 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 Sukhdeep K. Spall. The network helps show where Sukhdeep K. Spall may publish in the future.

Co-authorship network of co-authors of Sukhdeep K. Spall

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

All Works

12 of 12 papers shown
1.
Spall, Sukhdeep K., Ahmed Mohamed, Toby A. Dite, et al.. (2025). Quantitative Proteomic Analysis Unveils Protein Concentration Effects in Neat Urine Compared to Urine Extracellular Vesicles. Journal of Proteome Research. 24(7). 3343–3355.
3.
Ju, Yi, Hannah G. Kelly, Laura F. Dagley, et al.. (2020). Person-Specific Biomolecular Coronas Modulate Nanoparticle Interactions with Immune Cells in Human Blood. ACS Nano. 14(11). 15723–15737. 91 indexed citations
4.
Tanzer, Maria C., Nufail Khan, James Rickard, et al.. (2017). Combination of IAP antagonist and IFNγ activates novel caspase-10- and RIPK1-dependent cell death pathways. Cell Death and Differentiation. 24(3). 481–491. 38 indexed citations
5.
Lawlor, Kate E., Nufail Khan, Motti Gerlic, et al.. (2015). RIPK3 promotes cell death and NLRP3 inflammasome activation in the absence of MLKL. Nature Communications. 6(1). 6282–6282. 510 indexed citations breakdown →
6.
Etemadi, Nima, Michaël Chopin, Holly Anderton, et al.. (2015). TRAF2 regulates TNF and NF-κB signalling to suppress apoptosis and skin inflammation independently of Sphingosine kinase 1. eLife. 4. 88 indexed citations
7.
Hildebrand, Joanne M., Maria C. Tanzer, Isabelle S. Lucet, et al.. (2014). Activation of the pseudokinase MLKL unleashes the four-helix bundle domain to induce membrane localization and necroptotic cell death. Proceedings of the National Academy of Sciences. 111(42). 15072–15077. 468 indexed citations breakdown →
8.
Etemadi, Nima, James Rickard, Holly Anderton, et al.. (2014). 47. Cytokine. 70(1). 39–39. 1 indexed citations
9.
Schuenemann, Verena J., Reinhard Albrecht, Sukhdeep K. Spall, et al.. (2009). Structural basis of N‐end rule substrate recognition in Escherichia coli by the ClpAP adaptor protein ClpS. EMBO Reports. 10(6). 662–662. 2 indexed citations
10.
Schuenemann, Verena J., Reinhard Albrecht, Sukhdeep K. Spall, et al.. (2009). Structural basis of N‐end rule substrate recognition in Escherichia coli by the ClpAP adaptor protein ClpS. EMBO Reports. 10(5). 508–514. 74 indexed citations
11.
Ninnis, Robert L., Sukhdeep K. Spall, Gert Talbo, Kaye N. Truscott, & David A. Dougan. (2009). Modification of PATase by L/F‐transferase generates a ClpS‐dependent N‐end rule substrate in Escherichia coli. The EMBO Journal. 28(12). 1732–1744. 77 indexed citations
12.
Erbse, Annette H., Judith Wagner, Kaye N. Truscott, et al.. (2008). Conserved residues in the N‐domain of the AAA+ chaperone ClpA regulate substrate recognition and unfolding. FEBS Journal. 275(7). 1400–1410. 24 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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