Stefan K. Weidt

616 total citations
15 papers, 460 citations indexed

About

Stefan K. Weidt is a scholar working on Molecular Biology, Epidemiology and Public Health, Environmental and Occupational Health. According to data from OpenAlex, Stefan K. Weidt has authored 15 papers receiving a total of 460 indexed citations (citations by other indexed papers that have themselves been cited), including 8 papers in Molecular Biology, 7 papers in Epidemiology and 7 papers in Public Health, Environmental and Occupational Health. Recurrent topics in Stefan K. Weidt's work include Trypanosoma species research and implications (7 papers), Research on Leishmaniasis Studies (7 papers) and Metal complexes synthesis and properties (3 papers). Stefan K. Weidt is often cited by papers focused on Trypanosoma species research and implications (7 papers), Research on Leishmaniasis Studies (7 papers) and Metal complexes synthesis and properties (3 papers). Stefan K. Weidt collaborates with scholars based in United Kingdom, United States and Malaysia. Stefan K. Weidt's co-authors include Michael P. Barrett, Richard Burchmore, C. Logan Mackay, Pat R. R. Langridge‐Smith, Peter J. Sadler, Karl Burgess, Andrew W. Pountain, Fuyi Wang, Jingjing Xu and Nicholas J. Dickens and has published in prestigious journals such as Chemical Communications, International Journal of Molecular Sciences and PLoS Pathogens.

In The Last Decade

Stefan K. Weidt

15 papers receiving 458 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Stefan K. Weidt United Kingdom 12 179 168 166 79 74 15 460
Martin Winkler United States 12 99 0.6× 272 1.6× 55 0.3× 43 0.5× 39 0.5× 28 450
Rahul Modak India 12 31 0.2× 223 1.3× 87 0.5× 47 0.6× 33 0.4× 29 466
Kuan‐Yi Lu United States 12 39 0.2× 217 1.3× 126 0.8× 29 0.4× 21 0.3× 21 394
Nassira Mahmoudi France 12 52 0.3× 198 1.2× 224 1.3× 105 1.3× 74 1.0× 15 573
Santanu Sasidharan India 14 153 0.9× 221 1.3× 257 1.5× 100 1.3× 10 0.1× 35 585
Saravanan Vijayakumar India 12 78 0.4× 380 2.3× 108 0.7× 40 0.5× 11 0.1× 39 548
Jenicer K.U. Yokoyama-Yasunaka Brazil 18 300 1.7× 120 0.7× 528 3.2× 243 3.1× 29 0.4× 23 789
Elva Serna Paraguay 13 243 1.4× 110 0.7× 207 1.2× 264 3.3× 14 0.2× 17 466
Paula Faral‐Tello Uruguay 13 218 1.2× 94 0.6× 180 1.1× 92 1.2× 24 0.3× 23 364
Laurent Bonnac United States 14 117 0.7× 279 1.7× 41 0.2× 112 1.4× 48 0.6× 30 518

Countries citing papers authored by Stefan K. Weidt

Since Specialization
Citations

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

Fields of papers citing papers by Stefan K. Weidt

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Stefan K. Weidt

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

All Works

15 of 15 papers shown
1.
Tulloch, L.B., Michele Tinti, Richard J. Wall, et al.. (2024). Sterol 14-alpha demethylase (CYP51) activity in Leishmania donovani is likely dependent upon cytochrome P450 reductase 1. PLoS Pathogens. 20(7). e1012382–e1012382. 6 indexed citations
2.
Weidt, Stefan K., Richard Burchmore, Alan Kovačević, et al.. (2023). Metabolome Profiling in the Plasma of Dogs with Idiopathic Dilated Cardiomyopathy: A Multiplatform Mass-Spectrometry-Based Approach. International Journal of Molecular Sciences. 24(20). 15182–15182. 1 indexed citations
3.
Somani, Sukrut, Partha Laskar, Margaret Mullin, et al.. (2022). Limited Impact of the Protein Corona on the Cellular Uptake of PEGylated Zein Micelles by Melanoma Cancer Cells. Pharmaceutics. 14(2). 439–439. 12 indexed citations
4.
Ithnin, Nur Raihana, Wenbin Wei, Andrew W. Pountain, et al.. (2022). Amphotericin B resistance in Leishmania mexicana: Alterations to sterol metabolism and oxidative stress response. PLoS neglected tropical diseases. 16(9). e0010779–e0010779. 28 indexed citations
5.
Burchmore, Richard, Suzanne McGill, Stefan K. Weidt, et al.. (2021). Proteomic analysis reveals differentially abundant proteins probably involved in the virulence of amastigote and promastigote forms of Leishmania infantum. Parasitology Research. 120(2). 679–692. 8 indexed citations
6.
Pountain, Andrew W., Stefan K. Weidt, Clément Regnault, et al.. (2019). Genomic instability at the locus of sterol C24-methyltransferase promotes amphotericin B resistance in Leishmania parasites. PLoS neglected tropical diseases. 13(2). e0007052–e0007052. 43 indexed citations
7.
Mwenechanya, Roy, Julie Kovářová, Nicholas J. Dickens, et al.. (2017). Sterol 14α-demethylase mutation leads to amphotericin B resistance in Leishmania mexicana. PLoS neglected tropical diseases. 11(6). e0005649–e0005649. 47 indexed citations
8.
Mudaliar, Manikhandan, Riccardo Tassi, Funmilola Clara Thomas, et al.. (2016). Mastitomics, the integrated omics of bovine milk in an experimental model of Streptococcus uberis mastitis: 2. Label-free relative quantitative proteomics. Molecular BioSystems. 12(9). 2748–2761. 46 indexed citations
9.
Weidt, Stefan K., Dhilia Udie Lamasudin, Christina Naula, et al.. (2016). Integration of proteomics and metabolomics to elucidate metabolic adaptation in Leishmania. Journal of Proteomics. 155. 85–98. 26 indexed citations
10.
Oppermann, Madalina, Matthew J. Dalby, Richard Burchmore, et al.. (2015). Serially coupling hydrophobic interaction and reversed-phase chromatography with simultaneous gradients provides greater coverage of the metabolome. Metabolomics. 11(5). 1465–1470. 35 indexed citations
11.
Creek, Darren J., Muriel Mazet, Fiona Achcar, et al.. (2015). Probing the Metabolic Network in Bloodstream-Form Trypanosoma brucei Using Untargeted Metabolomics with Stable Isotope Labelled Glucose. PLoS Pathogens. 11(3). e1004689–e1004689. 97 indexed citations
12.
Wang, Fuyi, Jingjing Xu, Kui Wu, et al.. (2012). Competition between glutathione and DNA oligonucleotides for ruthenium(ii) arene anticancer complexes. Dalton Transactions. 42(9). 3188–3195. 45 indexed citations
13.
Goodwin, Richard J. A., Andrew R. Pitt, David J. Harrison, et al.. (2011). Matrix‐free mass spectrometric imaging using laser desorption ionisation Fourier transform ion cyclotron resonance mass spectrometry. Rapid Communications in Mass Spectrometry. 25(7). 969–972. 21 indexed citations
14.
Wang, Fuyi, Stefan K. Weidt, Jingjing Xu, et al.. (2008). Identification of clusters from reactions of ruthenium arene anticancer complex with glutathione using nanoscale liquid chromatography fourier transform ion cyclotron mass spectrometry combined with 18O-labeling. Journal of the American Society for Mass Spectrometry. 19(4). 544–549. 24 indexed citations
15.
Weidt, Stefan K., C. Logan Mackay, Pat R. R. Langridge‐Smith, & Peter J. Sadler. (2007). Platination of superoxide dismutase with cisplatin: tracking the ammonia ligands using Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS). Chemical Communications. 1719–1719. 21 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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