Simone König

4.2k total citations
144 papers, 3.0k citations indexed

About

Simone König is a scholar working on Molecular Biology, Spectroscopy and Cellular and Molecular Neuroscience. According to data from OpenAlex, Simone König has authored 144 papers receiving a total of 3.0k indexed citations (citations by other indexed papers that have themselves been cited), including 72 papers in Molecular Biology, 35 papers in Spectroscopy and 22 papers in Cellular and Molecular Neuroscience. Recurrent topics in Simone König's work include Advanced Proteomics Techniques and Applications (27 papers), Mass Spectrometry Techniques and Applications (26 papers) and Metabolomics and Mass Spectrometry Studies (12 papers). Simone König is often cited by papers focused on Advanced Proteomics Techniques and Applications (27 papers), Mass Spectrometry Techniques and Applications (26 papers) and Metabolomics and Mass Spectrometry Studies (12 papers). Simone König collaborates with scholars based in Germany, United States and South Africa. Simone König's co-authors include Henry M. Fales, Jon P. DeGnore, W C Barrett, Moon B. Yim, Yen-Fang Keng, Zhong‐Yin Zhang, Helmut Wieczorek, Axel Zeeck, Markus Huss and M. Gaßel and has published in prestigious journals such as Nature, Journal of Biological Chemistry and Circulation.

In The Last Decade

Simone König

139 papers receiving 3.0k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Simone König Germany 27 1.6k 408 319 310 238 144 3.0k
Stanley M. Stevens United States 28 1.9k 1.2× 611 1.5× 237 0.7× 316 1.0× 197 0.8× 98 3.4k
Mirella Trinei Italy 20 1.7k 1.0× 463 1.1× 183 0.6× 161 0.5× 207 0.9× 25 3.1k
Joëlle Vinh France 34 2.6k 1.6× 221 0.5× 267 0.8× 318 1.0× 157 0.7× 112 4.2k
Ivano Eberini Italy 36 2.6k 1.6× 449 1.1× 306 1.0× 462 1.5× 260 1.1× 151 4.4k
Giorgio Arrigoni Italy 36 2.3k 1.4× 330 0.8× 456 1.4× 255 0.8× 290 1.2× 149 4.1k
Jenny J. Yang United States 40 2.6k 1.6× 300 0.7× 269 0.8× 238 0.8× 285 1.2× 134 4.6k
Peter Gehrig Switzerland 40 2.2k 1.4× 230 0.6× 264 0.8× 503 1.6× 377 1.6× 81 4.6k
Mingjie Zhou China 19 1.4k 0.8× 362 0.9× 413 1.3× 154 0.5× 109 0.5× 43 2.9k
Xiaochun Zhu United States 29 2.8k 1.8× 534 1.3× 516 1.6× 212 0.7× 426 1.8× 73 4.6k
Dongmin Kang South Korea 32 2.3k 1.4× 291 0.7× 494 1.5× 279 0.9× 276 1.2× 101 4.2k

Countries citing papers authored by Simone König

Since Specialization
Citations

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

Fields of papers citing papers by Simone König

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Simone König

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

All Works

20 of 20 papers shown
1.
GÄde, Gerd, Simone König, & Heather G. Marco. (2025). Structural Diversity of Adipokinetic Hormones in the Coleopteran Suborder Polyphaga (Excluding Cucujiformia). Archives of Insect Biochemistry and Physiology. 118(3). e70049–e70049.
2.
König, Simone, Karin Schork, & Martin Eisenacher. (2024). Observations from the Proteomics Bench. Proteomes. 12(1). 6–6. 1 indexed citations
3.
König, Simone, et al.. (2024). Unraveling key steps in the biosynthesis of antimicrobial methylated unsaturated 2-alkyl-4-quinolones of Burkholderia thailandensis. Cell Reports Physical Science. 5(8). 102100–102100. 2 indexed citations
4.
Obermann, Wolfgang M.J., et al.. (2024). A change of rhodocytin's suprastructure turns the agonist into an antagonist of tumor cell induced platelet aggregation. The FASEB Journal. 38(2). e23402–e23402. 1 indexed citations
5.
König, Simone, et al.. (2023). The Renin–Angiotensin System in COVID-19: Can Long COVID Be Predicted?. Life. 13(7). 1462–1462. 2 indexed citations
6.
Marco, Heather G., Simone König, & Gerd GÄde. (2023). Predicted novel hypertrehalosaemic peptides of cockroaches are verified by mass spectrometry. Amino Acids. 55(11). 1641–1654. 3 indexed citations
7.
Bierhansl, Laura, Christina B. Schroeter, Venu Narayanan, et al.. (2023). NOX4-derived ROS are neuroprotective by balancing intracellular calcium stores. Cellular and Molecular Life Sciences. 80(5). 127–127. 13 indexed citations
8.
Black, David, et al.. (2023). Challenges in, and recommendations for, hyperspectral imaging in ex vivo malignant glioma biopsy measurements. Scientific Reports. 13(1). 3829–3829. 16 indexed citations
9.
Bierhansl, Laura, Matthias Pawlowski, Manuela Cerina, et al.. (2022). MMF induces antioxidative and anaplerotic pathways and is neuroprotective in hyperexcitability in vitro. Free Radical Biology and Medicine. 194. 337–346. 2 indexed citations
10.
Tepasse, Phil‐Robin, et al.. (2022). High Angiotensin-Converting Enzyme and Low Carboxypeptidase N Serum Activity Correlate with Disease Severity in COVID-19 Patients. Journal of Personalized Medicine. 12(3). 406–406. 7 indexed citations
11.
Mall, Achim, et al.. (2021). High CO2 levels drive the TCA cycle backwards towards autotrophy. Nature. 592(7856). 784–788. 119 indexed citations
12.
König, Simone, et al.. (2021). Reduced serum protease activity in Complex Regional Pain Syndrome: The impact of angiotensin-converting enzyme and carboxypeptidases. Journal of Pharmaceutical and Biomedical Analysis. 205. 114307–114307. 6 indexed citations
13.
König, Simone, et al.. (2021). Substance P Serum Degradation in Complex Regional Pain Syndrome – Another Piece of the Puzzle?. Journal of Pain. 23(3). 501–507. 8 indexed citations
14.
Šlais, Karel, et al.. (2015). pI-Control in Comparative Fluorescence Gel Electrophoresis (CoFGE) using amphoteric azo dyes. Data in Brief. 3. 221–228. 5 indexed citations
15.
König, Simone, et al.. (2014). Quantification of αS1-casein in breast milk using a targeted mass spectrometry-based approach. Journal of Pharmaceutical and Biomedical Analysis. 103. 52–58. 17 indexed citations
16.
17.
Volk, Gerd Fabian, et al.. (2008). Axonal regeneration in the organotypically cultured monkey retina: Biological aspects, dependence on substrates and age-related proteomic profiling. Restorative Neurology and Neuroscience. 26(4-5). 249–266. 14 indexed citations
18.
König, Simone. (2008). Target coatings and desorption surfaces in biomolecular MALDI‐MS. PROTEOMICS. 8(4). 706–714. 16 indexed citations
19.
Otte, Sören von, Jürgen R. J. Paletta, Steffi Becker, et al.. (2005). Follicular Fluid High Density Lipoprotein-associated Sphingosine 1-Phosphate Is a Novel Mediator of Ovarian Angiogenesis. Journal of Biological Chemistry. 281(9). 5398–5405. 60 indexed citations
20.
König, Simone, et al.. (2002). Isolation of total-RNA from formalin-fixed rat retina. Journal of Neuroscience Methods. 120(1). 55–63. 1 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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