Jacky B. Buckton

415 total citations
10 papers, 338 citations indexed

About

Jacky B. Buckton is a scholar working on Molecular Biology, Organic Chemistry and Oncology. According to data from OpenAlex, Jacky B. Buckton has authored 10 papers receiving a total of 338 indexed citations (citations by other indexed papers that have themselves been cited), including 5 papers in Molecular Biology, 4 papers in Organic Chemistry and 4 papers in Oncology. Recurrent topics in Jacky B. Buckton's work include Melanoma and MAPK Pathways (3 papers), Cytokine Signaling Pathways and Interactions (3 papers) and Synthesis of Tetrazole Derivatives (2 papers). Jacky B. Buckton is often cited by papers focused on Melanoma and MAPK Pathways (3 papers), Cytokine Signaling Pathways and Interactions (3 papers) and Synthesis of Tetrazole Derivatives (2 papers). Jacky B. Buckton collaborates with scholars based in United Kingdom, Australia and Germany. Jacky B. Buckton's co-authors include Paul Life, Katherine Bush, Marion C. Dickson, Inma Rioja, John R. Spaull, C Plater-Zyberk, Edward D. Zanders, Richard Angell, Kathryn J. Smith and Stuart Cockerill and has published in prestigious journals such as Journal of Medicinal Chemistry, IEEE Transactions on Medical Imaging and BMJ Open.

In The Last Decade

Jacky B. Buckton

10 papers receiving 327 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Jacky B. Buckton United Kingdom 8 126 84 78 74 49 10 338
Jordi Beleta Spain 7 104 0.8× 75 0.9× 24 0.3× 151 2.0× 118 2.4× 7 447
Masako Kuno Japan 14 291 2.3× 109 1.3× 47 0.6× 101 1.4× 90 1.8× 25 614
Gilbert C. Olini United States 7 188 1.5× 70 0.8× 23 0.3× 291 3.9× 107 2.2× 8 539
John W. Rice United States 9 338 2.7× 37 0.4× 18 0.2× 60 0.8× 81 1.7× 12 473
Stephen Rapecki United Kingdom 7 101 0.8× 53 0.6× 44 0.6× 12 0.2× 113 2.3× 11 272
Chiemi Mishima-Tsumagari Japan 11 186 1.5× 22 0.3× 28 0.4× 45 0.6× 54 1.1× 16 340
Jane McPheat United Kingdom 15 379 3.0× 70 0.8× 18 0.2× 15 0.2× 65 1.3× 18 583
Olga V. Trubetskoy United States 10 221 1.8× 67 0.8× 26 0.3× 12 0.2× 18 0.4× 12 393
Masaki Gouda Japan 9 235 1.9× 85 1.0× 11 0.1× 49 0.7× 28 0.6× 11 385
Adam J. Stein United States 11 418 3.3× 43 0.5× 28 0.4× 59 0.8× 51 1.0× 13 603

Countries citing papers authored by Jacky B. Buckton

Since Specialization
Citations

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

Fields of papers citing papers by Jacky B. Buckton

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jacky B. Buckton. 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 Jacky B. Buckton. The network helps show where Jacky B. Buckton may publish in the future.

Co-authorship network of co-authors of Jacky B. Buckton

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

All Works

10 of 10 papers shown
1.
Anie, Kofi A., Jacky B. Buckton, Mark Layton, et al.. (2016). SWIM (sickle with ibuprofen and morphine) randomised controlled trial fails to recruit: lessons learnt. BMJ Open. 6(6). e011276–e011276. 4 indexed citations
2.
Triantaphyllopoulos, Kostas A., Leigh A. Madden, Inmaculada Rioja, et al.. (2010). In vitro target validation and in vivo efficacy of p38 MAP kinase inhibition in established chronic collagen-induced arthritis model: a pre-clinical study.. PubMed. 28(2). 176–85. 8 indexed citations
3.
Angell, Richard, Paul Bamborough, Jacky B. Buckton, et al.. (2008). Biphenyl amide p38 kinase inhibitors 3: Improvement of cellular and in vivo activity. Bioorganic & Medicinal Chemistry Letters. 18(15). 4428–4432. 63 indexed citations
4.
Priest, Richard, John R. Spaull, Jacky B. Buckton, et al.. (2008). Immunomodulatory activity of a methionine aminopeptidase-2 inhibitor on B cell differentiation. Clinical & Experimental Immunology. 155(3). 514–522. 12 indexed citations
5.
Angell, Richard, Paul Bamborough, David Brown, et al.. (2007). Biphenyl amide p38 kinase inhibitors 2: Optimisation and SAR. Bioorganic & Medicinal Chemistry Letters. 18(1). 324–328. 24 indexed citations
6.
Leung, Kelvin K., Mark P. Holden, Nadeem Saeed, et al.. (2006). Automatic Quantification of Changes in Bone in Serial MR Images of Joints. IEEE Transactions on Medical Imaging. 25(12). 1617–1626. 14 indexed citations
7.
Leung, Karen Ka Yan, Rolf A. Heckemann, Nermin Kamal Saeed, et al.. (2005). Analysis of serial MR images of joints. 2. 221–224. 2 indexed citations
8.
Rioja, Inma, Katherine Bush, Jacky B. Buckton, Marion C. Dickson, & Paul Life. (2004). Joint cytokine quantification in two rodent arthritis models: kinetics of expression, correlation of mRNA and protein levels and response to prednisolone treatment. Clinical & Experimental Immunology. 137(1). 65–73. 107 indexed citations
9.
Plater-Zyberk, C, et al.. (2001). Amelioration of arthritis in two murine models using antibodies to Oncostatin M. Arthritis & Rheumatism. 44(11). 2697–2702. 68 indexed citations
10.

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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