Vikki Flemington

912 total citations · 1 hit paper
9 papers, 546 citations indexed

About

Vikki Flemington is a scholar working on Molecular Biology, Surgery and Cell Biology. According to data from OpenAlex, Vikki Flemington has authored 9 papers receiving a total of 546 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Molecular Biology, 2 papers in Surgery and 2 papers in Cell Biology. Recurrent topics in Vikki Flemington's work include Protein Kinase Regulation and GTPase Signaling (3 papers), Melanoma and MAPK Pathways (2 papers) and PI3K/AKT/mTOR signaling in cancer (2 papers). Vikki Flemington is often cited by papers focused on Protein Kinase Regulation and GTPase Signaling (3 papers), Melanoma and MAPK Pathways (2 papers) and PI3K/AKT/mTOR signaling in cancer (2 papers). Vikki Flemington collaborates with scholars based in United Kingdom, Brazil and United States. Vikki Flemington's co-authors include Richard A. Ward, Paul D. Smith, Darren McKerrecher, Stephen E. Fawell, Nicolas Floc’h, Ian G. Ganley, Matthew King, Karen Roberts, Christopher R. Jones and Gary Fairley and has published in prestigious journals such as Chemical Reviews, Nature Communications and Cancer Research.

In The Last Decade

Vikki Flemington

9 papers receiving 537 citations

Hit Papers

Challenges and Opportunities in Cancer Drug Resistance 2020 2026 2022 2024 2020 100 200 300

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Vikki Flemington United Kingdom 6 337 107 106 82 63 9 546
Tse J. Wong Netherlands 8 169 0.5× 187 1.7× 117 1.1× 68 0.8× 63 1.0× 9 416
Xuan Qin China 12 354 1.1× 128 1.2× 78 0.7× 34 0.4× 60 1.0× 25 481
Jessica Iegre United Kingdom 14 533 1.6× 167 1.6× 180 1.7× 47 0.6× 47 0.7× 19 707
Seojeong Park South Korea 14 318 0.9× 165 1.5× 178 1.7× 43 0.5× 54 0.9× 33 578
Céline Bouclier France 11 258 0.8× 91 0.9× 106 1.0× 64 0.8× 34 0.5× 14 512
Ada W.Y. Leung Canada 17 300 0.9× 275 2.6× 174 1.6× 95 1.2× 53 0.8× 30 720
Dehua Lu China 16 311 0.9× 165 1.5× 67 0.6× 86 1.0× 49 0.8× 29 575
Elin Lindhagen Sweden 14 245 0.7× 138 1.3× 50 0.5× 41 0.5× 67 1.1× 28 505
Alan Bilsland United Kingdom 21 698 2.1× 120 1.1× 67 0.6× 30 0.4× 105 1.7× 37 988

Countries citing papers authored by Vikki Flemington

Since Specialization
Citations

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

Fields of papers citing papers by Vikki Flemington

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Vikki Flemington

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

All Works

9 of 9 papers shown
1.
Davies, Gareth M., Tiziana Monteverde, Jonathan Tart, et al.. (2024). High throughput application of the NanoBiT Biochemical Assay for the discovery of selective inhibitors of the interaction of PI3K-p110α with KRAS. SLAS DISCOVERY. 29(8). 100197–100197. 1 indexed citations
2.
Andrews, David, Sabina Cosulich, Nullin Divecha, et al.. (2021). Identification and optimization of a novel series of selective PIP5K inhibitors. Bioorganic & Medicinal Chemistry. 54. 116557–116557. 7 indexed citations
3.
Saunders, Alex M., David Barneda, Vikki Flemington, et al.. (2020). Development of isotope-enriched phosphatidylinositol-4- and 5-phosphate cellular mass spectrometry probes. Chemical Science. 12(7). 2549–2557. 4 indexed citations
4.
Ward, Richard A., Stephen E. Fawell, Nicolas Floc’h, et al.. (2020). Challenges and Opportunities in Cancer Drug Resistance. Chemical Reviews. 121(6). 3297–3351. 330 indexed citations breakdown →
5.
Sale, Matthew J., Noel R. Monks, Rebecca Gilley, et al.. (2019). Targeting melanoma’s MCL1 bias unleashes the apoptotic potential of BRAF and ERK1/2 pathway inhibitors. Nature Communications. 10(1). 5167–5167. 51 indexed citations
6.
King, Matthew, Ian G. Ganley, & Vikki Flemington. (2016). Inhibition of cholesterol metabolism underlies synergy between mTOR pathway inhibition and chloroquine in bladder cancer cells. Oncogene. 35(34). 4518–4528. 48 indexed citations
7.
Ward, Richard A., Nicola Colclough, Mairi Challinor, et al.. (2015). Structure-Guided Design of Highly Selective and Potent Covalent Inhibitors of ERK1/2. Journal of Medicinal Chemistry. 58(11). 4790–4801. 74 indexed citations
8.
Waring, Michael J., Darren A.E. Cross, David Andrews, et al.. (2013). Abstract 2228: Phosphatidylinositol-4-kinase - Potent and selective inhibitors of PI4Kα and PI4Kβ.. Cancer Research. 73(8_Supplement). 2228–2228. 1 indexed citations
9.
Waring, Michael J., David Andrews, Paul Faulder, et al.. (2013). Potent, selective small molecule inhibitors of type III phosphatidylinositol-4-kinase α- but not β-inhibit the phosphatidylinositol signaling cascade and cancer cell proliferation. Chemical Communications. 50(40). 5388–5390. 30 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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