Johannes Müthing

5.2k total citations · 1 hit paper
128 papers, 4.0k citations indexed

About

Johannes Müthing is a scholar working on Molecular Biology, Endocrinology and Immunology. According to data from OpenAlex, Johannes Müthing has authored 128 papers receiving a total of 4.0k indexed citations (citations by other indexed papers that have themselves been cited), including 94 papers in Molecular Biology, 43 papers in Endocrinology and 28 papers in Immunology. Recurrent topics in Johannes Müthing's work include Glycosylation and Glycoproteins Research (78 papers), Escherichia coli research studies (43 papers) and Viral gastroenteritis research and epidemiology (22 papers). Johannes Müthing is often cited by papers focused on Glycosylation and Glycoproteins Research (78 papers), Escherichia coli research studies (43 papers) and Viral gastroenteritis research and epidemiology (22 papers). Johannes Müthing collaborates with scholars based in Germany, Croatia and United States. Johannes Müthing's co-authors include Jasna Peter‐Katalinić, Helge Karch, Klaus Dreisewerd, Iris Meisen, Gottfried Pohlentz, Jens Soltwisch, Ute Distler, Peter F. Mühlradt, Michael Mormann and Alexander W. Friedrich and has published in prestigious journals such as Science, Journal of Biological Chemistry and The Journal of Immunology.

In The Last Decade

Johannes Müthing

128 papers receiving 3.9k citations

Hit Papers

Mass spectrometry imaging with laser-induced postionization 2015 2026 2018 2022 2015 50 100 150 200 250

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Johannes Müthing Germany 37 2.4k 984 755 749 593 128 4.0k
Wolfgang Peti United States 46 5.3k 2.2× 601 0.6× 729 1.0× 696 0.9× 417 0.7× 144 7.3k
Haydn L. Ball United States 30 4.3k 1.8× 340 0.3× 409 0.5× 327 0.4× 130 0.2× 57 5.7k
Günter Schmidt Germany 15 2.3k 0.9× 413 0.4× 1.2k 1.5× 837 1.1× 164 0.3× 22 4.0k
Daniel Wall United States 39 3.2k 1.3× 569 0.6× 471 0.6× 234 0.3× 138 0.2× 85 4.6k
F. Pattus France 51 4.3k 1.8× 391 0.4× 252 0.3× 742 1.0× 452 0.8× 119 6.2k
Pei Zhou United States 50 4.3k 1.8× 194 0.2× 411 0.5× 510 0.7× 234 0.4× 217 6.5k
Francis Impens Belgium 40 2.9k 1.2× 186 0.2× 506 0.7× 734 1.0× 209 0.4× 116 4.4k
Hervé Drobecq France 36 2.3k 1.0× 104 0.1× 394 0.5× 622 0.8× 357 0.6× 122 4.4k
Rebecca Page United States 42 4.1k 1.7× 533 0.5× 157 0.2× 695 0.9× 398 0.7× 117 5.9k
Elena N. Kitova Canada 35 2.1k 0.9× 197 0.2× 1.8k 2.4× 239 0.3× 337 0.6× 123 3.5k

Countries citing papers authored by Johannes Müthing

Since Specialization
Citations

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

Fields of papers citing papers by Johannes Müthing

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Johannes Müthing

This figure shows the co-authorship network connecting the top 25 collaborators of Johannes Müthing. A scholar is included among the top collaborators of Johannes Müthing 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 Johannes Müthing. Johannes Müthing 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.
Pohlentz, Gottfried, et al.. (2021). Thin-Layer Chromatography in Structure and Recognition Studies of Shiga Toxin Glycosphingolipid Receptors. Methods in molecular biology. 2291. 229–252. 7 indexed citations
2.
Bien, Tanja, Markus Perl, Ulrich Nitsche, et al.. (2020). MALDI-2 Mass Spectrometry and Immunohistochemistry Imaging of Gb3Cer, Gb4Cer, and Further Glycosphingolipids in Human Colorectal Cancer Tissue. Analytical Chemistry. 92(10). 7096–7105. 36 indexed citations
3.
Humpf, Hans‐Ulrich, et al.. (2016). Shiga toxin glycosphingolipid receptors and their lipid membrane ensemble in primary human blood–brain barrier endothelial cells. Glycobiology. 27(1). 99–109. 29 indexed citations
4.
Körsgen, Martin, et al.. (2014). Characterization of freeze-fractured epithelial plasma membranes on nanometer scale with ToF-SIMS. Analytical and Bioanalytical Chemistry. 407(8). 2203–2211. 29 indexed citations
5.
Müthing, Johannes, Iris Meisen, Wenlan Zhang, et al.. (2012). Promiscuous Shiga toxin 2e and its intimate relationship to Forssman. Glycobiology. 22(6). 849–862. 50 indexed citations
6.
Hoffmann, Petra, Jerzy–Roch Nofer, Gottfried Pohlentz, et al.. (2010). Neutral glycosphingolipids in human blood: a precise mass spectrometry analysis with special reference to lipoprotein-associated Shiga toxin receptors. Journal of Lipid Research. 51(8). 2282–2294. 35 indexed citations
7.
Distler, Ute, Irena Drmić Hofman, Jörg Haier, et al.. (2009). Shiga Toxin Receptor Gb3Cer/CD77: Tumor-Association and Promising Therapeutic Target in Pancreas and Colon Cancer. PLoS ONE. 4(8). e6813–e6813. 67 indexed citations
8.
Distler, Ute, Irena Drmić Hofman, Jörg Haier, et al.. (2008). Tumor-associated CD75s- and iso-CD75s-gangliosides are potential targets for adjuvant therapy in pancreatic cancer. Molecular Cancer Therapeutics. 7(8). 2464–2475. 26 indexed citations
10.
Müthing, Johannes, Bettina Möckel, Martin Langer, et al.. (2002). Preferential binding of the anticancer drug rViscumin (recombinant mistletoe lectin) to terminally  2-6-sialylated neolacto-series gangliosides. Glycobiology. 12(8). 485–497. 41 indexed citations
11.
Müthing, Johannes. (2000). Analyses of Glycosphingollpids by High-Performance Liquid Chromatography. Methods in enzymology on CD-ROM/Methods in enzymology. 312. 45–64. 26 indexed citations
12.
Müthing, Johannes, et al.. (1998). Glycosphingolipids of skeletal muscle: I. Subcellular distribution of neutral glycosphingolipids and gangliosides in rabbit skeletal muscle. Carbohydrate Research. 307(1-2). 135–145. 13 indexed citations
13.
Müthing, Johannes, et al.. (1997). Glycosphingolipid expression in human skeletal and heart muscle assessed by immunostaining thin-layer chromatography. Glycoconjugate Journal. 14(1). 19–28. 24 indexed citations
14.
Müthing, Johannes. (1997). Neutral glycosphingolipids and gangliosides from spleen T lymphoblasts of genetically different inbred mouse strains. Glycoconjugate Journal. 14(2). 241–248. 6 indexed citations
15.
Müthing, Johannes, et al.. (1996). Sialidase Activity in Culture Fluid of Chinese Hamster Ovary Cells during Batch Culture and Its Effect on Recombinant Human Antithrombin III Integrity. Biotechnology Progress. 12(4). 559–563. 36 indexed citations
16.
Müthing, Johannes. (1994). Improved thin-layer chromatographic separation of gangliosides by automated multiple development. Journal of Chromatography B Biomedical Sciences and Applications. 657(1). 75–81. 11 indexed citations
17.
Müthing, Johannes, et al.. (1994). Different Distributions of Glycosphingolipids in Mouse and Rabbit Skeletal Muscle Demonstrated by Biochemical and Immunohistological Analyses1. The Journal of Biochemistry. 115(2). 248–256. 37 indexed citations
18.
Steuer, Heiko, et al.. (1992). Structural characterization of gangliosides from B cell derived cell lines. Biological Chemistry Hoppe-Seyler. 373(9). 272–4. 1 indexed citations
20.
Müthing, Johannes, et al.. (1989). Gangliosides of murine T lymphocyte subpopulations. Biochemistry. 28(7). 2923–2929. 45 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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