Volker Gnau

6.6k total citations
31 papers, 1.5k citations indexed

About

Volker Gnau is a scholar working on Molecular Biology, Immunology and Spectroscopy. According to data from OpenAlex, Volker Gnau has authored 31 papers receiving a total of 1.5k indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Molecular Biology, 11 papers in Immunology and 6 papers in Spectroscopy. Recurrent topics in Volker Gnau's work include Immune Cell Function and Interaction (9 papers), T-cell and B-cell Immunology (9 papers) and Immunotherapy and Immune Responses (7 papers). Volker Gnau is often cited by papers focused on Immune Cell Function and Interaction (9 papers), T-cell and B-cell Immunology (9 papers) and Immunotherapy and Immune Responses (7 papers). Volker Gnau collaborates with scholars based in Germany, United States and Japan. Volker Gnau's co-authors include Kirsten Falk, Günther Jung, Stefan Stevanović, Olaf Rötzschke, G. Jung, Hans‐Georg Rammensee, Hans-Georg Rammensee, Jörg W. Metzger, Georg Malcherek and Arthur Melms and has published in prestigious journals such as Proceedings of the National Academy of Sciences, Journal of Biological Chemistry and The Journal of Experimental Medicine.

In The Last Decade

Volker Gnau

31 papers receiving 1.5k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Volker Gnau Germany 24 747 710 171 143 128 31 1.5k
Melanie A. Sherman United States 20 682 0.9× 490 0.7× 81 0.5× 33 0.2× 79 0.6× 28 1.4k
Kiyoshi Miwa Japan 25 666 0.9× 902 1.3× 91 0.5× 62 0.4× 74 0.6× 84 1.8k
Søren Bregenholt Denmark 19 504 0.7× 467 0.7× 212 1.2× 28 0.2× 90 0.7× 31 1.3k
A. R. Sanderson United Kingdom 23 756 1.0× 733 1.0× 352 2.1× 57 0.4× 48 0.4× 58 1.7k
Tateshi Kataoka Japan 20 973 1.3× 656 0.9× 109 0.6× 28 0.2× 49 0.4× 74 1.7k
R. C. Ting United States 22 555 0.7× 1.5k 2.1× 175 1.0× 64 0.4× 37 0.3× 51 2.6k
Geoffrey Yarranton United States 29 193 0.3× 1.7k 2.4× 321 1.9× 53 0.4× 30 0.2× 53 2.5k
William D. Tolbert United States 24 363 0.5× 650 0.9× 243 1.4× 67 0.5× 22 0.2× 59 1.3k
Rolf Swoboda United States 21 564 0.8× 554 0.8× 71 0.4× 24 0.2× 72 0.6× 43 1.4k
Mitsuo Hayakawa Japan 19 238 0.3× 551 0.8× 101 0.6× 47 0.3× 86 0.7× 74 1.4k

Countries citing papers authored by Volker Gnau

Since Specialization
Citations

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

Fields of papers citing papers by Volker Gnau

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Volker Gnau

This figure shows the co-authorship network connecting the top 25 collaborators of Volker Gnau. A scholar is included among the top collaborators of Volker Gnau 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 Volker Gnau. Volker Gnau 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.
Tolson, Jonathan, Thomas Flad, Volker Gnau, et al.. (2005). Differential detection of S100A8 in transitional cell carcinoma of the bladder by pair wise tissue proteomic and immunohistochemical analysis. PROTEOMICS. 6(2). 697–708. 59 indexed citations
2.
Wiesmüller, Karl‐Heinz, Volker Gnau, Günther Jung, et al.. (2001). AMP deaminase in rat brain: Localization in neurons and ependymal cells. Journal of Neuroscience Research. 66(5). 941–950. 14 indexed citations
3.
4.
5.
Friede, Thomas, Volker Gnau, Günther Jung, et al.. (1996). Natural ligand motifs of closely related HLA-DR4 molecules predict features of rheumatoid arthritis associated peptides. Biochimica et Biophysica Acta (BBA) - Molecular Basis of Disease. 1316(2). 85–101. 52 indexed citations
6.
Kuipers, Oscar P., Gabriele Bierbaum, Birgit Ottenwälder, et al.. (1996). Protein engineering of lantibiotics. Antonie van Leeuwenhoek. 69(2). 161–170. 104 indexed citations
7.
Klumpp, Susanne, et al.. (1996). Cathepsin L is an Intracellular and Extracellular Protease in Paramecium Tetraurelia. European Journal of Biochemistry. 238(1). 198–206. 26 indexed citations
8.
Gnau, Volker, et al.. (1996). Biochemical and molecular characterization of the extracellular esterase from Streptomyces diastatochromogenes. Journal of Bacteriology. 178(7). 1858–1865. 31 indexed citations
9.
Friede, Thomas, Volker Gnau, Günther Jung, et al.. (1996). Natural ligand motifs of closely related HLA-DR4 molecules predict features of rheumatoid arthritis associated peptides. Human Immunology. 47(1-2). 76–76. 1 indexed citations
10.
Joos, Thomas, Charles A. Whittaker, Fanying Meng, et al.. (1995). Integrin α5 during early development of Xenopus laevis. Mechanisms of Development. 50(2-3). 187–199. 41 indexed citations
11.
Malcherek, Georg, Volker Gnau, G. Jung, Hans‐Georg Rammensee, & Arthur Melms. (1995). Supermotifs enable natural invariant chain-derived peptides to interact with many major histocompatibility complex-class II molecules.. The Journal of Experimental Medicine. 181(2). 527–536. 105 indexed citations
12.
Falk, Kirsten, Olaf Rötzschke, Masafumi Takiguchi, et al.. (1995). Peptide motifs of HLA-B51, -B52 and -B78 molecules, and implications for Behfet's disease. International Immunology. 7(2). 223–228. 75 indexed citations
13.
Steinle, Alexander, Kirsten Falk, Olaf Rötzschke, et al.. (1995). Motif of HLA-B*3503 peptide ligands. Immunogenetics. 43(1-2). 105–107. 31 indexed citations
14.
Ottenwälder, Birgit, Thomas Kupke, Volker Gnau, et al.. (1995). Isolation and characterization of genetically engineered gallidermin and epidermin analogs. Applied and Environmental Microbiology. 61(11). 3894–3903. 61 indexed citations
15.
Ilg, Thomas, et al.. (1994). Distribution of parasite cysteine proteinases in lesions of mice infected with Leishmania mexicana amastigotes. Molecular and Biochemical Parasitology. 67(2). 193–203. 34 indexed citations
16.
Falk, Kirsten, Olaf Rötzschke, Masafumi Takiguchi, et al.. (1994). Peptide motifs of HLA-A1,-A11,-A31, and-A33 molecules. Immunogenetics. 40(3). 238–241. 74 indexed citations
17.
Halder, Thomas, et al.. (1994). A 16mer peptide of the human autoantigen calreticulin is a most prominent HLA-DR4Dw4-associated self-peptide. Human Immunology. 41(1). 39–45. 25 indexed citations
18.
Maier, Reinhard, Kirsten Falk, Olaf Rötzschke, et al.. (1994). Peptide motifs of HLA-A3, -A24, and -B7 molecules as determined by pool sequencing. Immunogenetics. 40(4). 306–308. 66 indexed citations
19.
Falk, Kirsten, Olaf Rötzschke, Stefan Stevanović, et al.. (1994). Analysis of a naturally occurring HLA class I-restricted viral epitope.. PubMed. 82(3). 337–42. 23 indexed citations
20.
Malcherek, Georg, Kirsten Falk, Hans-Georg Rammensee, et al.. (1993). Natural peptide ligand motifs of two HLA molecules associated with myasthenia gravis. International Immunology. 5(10). 1229–1237. 53 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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