Jamie J.L. Williams

460 total citations
8 papers, 344 citations indexed

About

Jamie J.L. Williams is a scholar working on Oncology, Molecular Biology and Immunology. According to data from OpenAlex, Jamie J.L. Williams has authored 8 papers receiving a total of 344 indexed citations (citations by other indexed papers that have themselves been cited), including 6 papers in Oncology, 3 papers in Molecular Biology and 3 papers in Immunology. Recurrent topics in Jamie J.L. Williams's work include Cytokine Signaling Pathways and Interactions (6 papers), interferon and immune responses (3 papers) and Cell Adhesion Molecules Research (2 papers). Jamie J.L. Williams is often cited by papers focused on Cytokine Signaling Pathways and Interactions (6 papers), interferon and immune responses (3 papers) and Cell Adhesion Molecules Research (2 papers). Jamie J.L. Williams collaborates with scholars based in United Kingdom, France and Germany. Jamie J.L. Williams's co-authors include Timothy M. Palmer, Talat Nasim, Ian P. Salt, George S. Baillie, Kirsten Riches‐Suman, Benoı̂t Viollet, Simon A. Hawley, Marie-Ann Ewart, Christian Delles and Ana P. Costa‐Pereira and has published in prestigious journals such as Nature Communications, Trends in Pharmacological Sciences and Pharmacological Research.

In The Last Decade

Jamie J.L. Williams

8 papers receiving 341 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Jamie J.L. Williams United Kingdom	7	177	114	111	47	40	8	344
Hiromichi Nagano Japan	8	228 1.3×	104 0.9×	74 0.7×	67 1.4×	75 1.9×	9	426
Tianjiao Sun United States	10	288 1.6×	116 1.0×	74 0.7×	64 1.4×	27 0.7×	15	479
Laia Trigueros‐Motos Spain	10	190 1.1×	52 0.5×	81 0.7×	28 0.6×	42 1.1×	11	335
Shuijie Li China	13	248 1.4×	91 0.8×	96 0.9×	139 3.0×	55 1.4×	31	466
Zakar Mnjoyan United States	8	167 0.9×	94 0.8×	58 0.5×	67 1.4×	24 0.6×	9	389
Yuniel Fernández‐Marrero Switzerland	13	203 1.1×	147 1.3×	59 0.5×	54 1.1×	41 1.0×	22	389
Yan Dai China	10	182 1.0×	99 0.9×	124 1.1×	84 1.8×	20 0.5×	19	421
Seok-Jun Kim South Korea	8	314 1.8×	142 1.2×	102 0.9×	89 1.9×	32 0.8×	8	456
Chiyuki Akiyama Japan	6	154 0.9×	173 1.5×	124 1.1×	64 1.4×	46 1.1×	9	392
Harika Sabbineni United States	12	344 1.9×	66 0.6×	78 0.7×	94 2.0×	30 0.8×	16	535

Countries citing papers authored by Jamie J.L. Williams

Since Specialization

Citations

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

Fields of papers citing papers by Jamie J.L. Williams

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jamie J.L. Williams. 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 Jamie J.L. Williams. The network helps show where Jamie J.L. Williams may publish in the future.

Co-authorship network of co-authors of Jamie J.L. Williams

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

All Works

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8 of 8 papers shown

Williams, Jamie J.L., George S. Baillie, & Timothy M. Palmer. (2020). Investigation of Novel Cavin-1/Suppressor of Cytokine Signaling 3 (SOCS3) Interactions by Coimmunoprecipitation, Peptide Pull-Down, and Peptide Array Overlay Approaches. Methods in molecular biology. 2169. 105–118. 1 indexed citations

Williams, Jamie J.L., et al.. (2019). Targeting SOCS Proteins to Control JAK-STAT Signalling in Disease. Trends in Pharmacological Sciences. 40(5). 298–308. 137 indexed citations

Williams, Jamie J.L., William Mullen, Richard Burchmore, et al.. (2018). Interaction of suppressor of cytokine signalling 3 with cavin-1 links SOCS3 function and cavin-1 stability. Nature Communications. 9(1). 168–168. 23 indexed citations

Williams, Jamie J.L., et al.. (2017). Linking energy sensing to suppression of JAK-STAT signalling: A potential route for repurposing AMPK activators?. Pharmacological Research. 128. 88–100. 41 indexed citations

Rutherford, Claire, Jamie J.L. Williams, Marie-Ann Ewart, et al.. (2016). Phosphorylation of Janus kinase 1 (JAK1) by AMP-activated protein kinase (AMPK) links energy sensing to anti-inflammatory signaling. Science Signaling. 9(453). ra109–ra109. 82 indexed citations

Williams, Jamie J.L., et al.. (2014). Role of Ubiquitylation in Controlling Suppressor of Cytokine Signalling 3 (SOCS3) Function and Expression. Cells. 3(2). 546–562. 31 indexed citations

Williams, Jamie J.L. & Timothy M. Palmer. (2014). Cavin-1: caveolae-dependent signalling and cardiovascular disease. Biochemical Society Transactions. 42(2). 284–288. 19 indexed citations

Williams, Jamie J.L. & Timothy M. Palmer. (2012). Unbiased identification of substrates for the Epac1-inducible E3 ubiquitin ligase component SOCS-3. Biochemical Society Transactions. 40(1). 215–218. 10 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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