Norbert Koch

1.7k total citations
62 papers, 1.5k citations indexed

About

Norbert Koch is a scholar working on Immunology, Molecular Biology and Radiology, Nuclear Medicine and Imaging. According to data from OpenAlex, Norbert Koch has authored 62 papers receiving a total of 1.5k indexed citations (citations by other indexed papers that have themselves been cited), including 37 papers in Immunology, 29 papers in Molecular Biology and 23 papers in Radiology, Nuclear Medicine and Imaging. Recurrent topics in Norbert Koch's work include Monoclonal and Polyclonal Antibodies Research (22 papers), T-cell and B-cell Immunology (22 papers) and Immunotherapy and Immune Responses (21 papers). Norbert Koch is often cited by papers focused on Monoclonal and Polyclonal Antibodies Research (22 papers), T-cell and B-cell Immunology (22 papers) and Immunotherapy and Immune Responses (21 papers). Norbert Koch collaborates with scholars based in Germany, New Zealand and Portugal. Norbert Koch's co-authors include Günter J. Hämmerling, Anna Maria Eis‐Hübinger, Jürgen Neumann, Susanne Koch, Ulrich Pessara, Alexander D. McLellan, Sebastian Temme, Brigitta Stockinger, Jüri Habicht and Manuel Grez and has published in prestigious journals such as Nature, Cell and Journal of Biological Chemistry.

In The Last Decade

Norbert Koch

61 papers receiving 1.4k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Norbert Koch Germany 20 892 594 260 180 117 62 1.5k
N. Koch Germany 22 1.1k 1.2× 519 0.9× 310 1.2× 98 0.5× 135 1.2× 42 1.6k
Bärbel S. Blaum Germany 22 927 1.0× 563 0.9× 132 0.5× 166 0.9× 110 0.9× 36 1.9k
Navin Varadarajan United States 24 598 0.7× 832 1.4× 301 1.2× 105 0.6× 59 0.5× 62 1.8k
John F. Beausang United States 19 492 0.6× 1000 1.7× 290 1.1× 69 0.4× 49 0.4× 48 1.8k
Jin‐Hwan Han United States 14 781 0.9× 236 0.4× 136 0.5× 676 3.8× 41 0.4× 27 1.7k
Gordon Stamp United Kingdom 16 311 0.3× 669 1.1× 180 0.7× 126 0.7× 22 0.2× 28 1.5k
Vincenzo Di Bartolo France 28 1.4k 1.6× 722 1.2× 183 0.7× 213 1.2× 18 0.2× 52 2.2k
Veronika I. Zarnitsyna United States 23 783 0.9× 428 0.7× 293 1.1× 187 1.0× 28 0.2× 47 1.8k
Padmaja Mehta United States 14 787 0.9× 1.1k 1.8× 218 0.8× 76 0.4× 15 0.1× 16 1.7k
W. Hertz Germany 13 753 0.8× 429 0.7× 279 1.1× 47 0.3× 36 0.3× 23 1.3k

Countries citing papers authored by Norbert Koch

Since Specialization
Citations

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

Fields of papers citing papers by Norbert Koch

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Norbert Koch

This figure shows the co-authorship network connecting the top 25 collaborators of Norbert Koch. A scholar is included among the top collaborators of Norbert Koch 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 Norbert Koch. Norbert Koch 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.
Temme, Sebastian, et al.. (2019). Assembly, Intracellular Transport, and Release of MHC Class II Peptide Receptors. Methods in molecular biology. 1988. 297–314. 5 indexed citations
2.
3.
Koch, Norbert, et al.. (2011). Stoichiometry of HLA Class II-Invariant Chain Oligomers. PLoS ONE. 6(2). e17257–e17257. 16 indexed citations
4.
Ting, Yi Tian, Sebastian Temme, Norbert Koch, & Alexander D. McLellan. (2009). A New Monoclonal Antibody Recognizing a Linear Determinant on the HLA-DRα Chain N-terminus. Hybridoma. 28(6). 423–429. 4 indexed citations
5.
Karaüzüm, Hatice, Elisa Monzón‐Casanova, Ronald Rudolf, et al.. (2008). Superantigen‐presentation by rat major histocompatibility complex class II molecules RT1.Bl and RT1.Dl. Immunology. 128(1pt2). e572–81. 3 indexed citations
6.
Nagaraj, Srinivas, Susanne Frank, Carsten Ziske, et al.. (2008). Pancreas Carcinoma Antigen Fused to Invariant Chain Elicits T-Cell Response and Tumor Growth Inhibition. Pancreas. 37(3). 321–327. 5 indexed citations
7.
Neumann, Jürgen & Norbert Koch. (2005). Assembly of major histocompatibility complex class II subunits with invariant chain. FEBS Letters. 579(27). 6055–6059. 16 indexed citations
8.
Laurie, Karen, Nicole L. La Gruta, Norbert Koch, Ian R. van Driel, & Paul A. Gleeson. (2004). Thymic Expression of a Gastritogenic Epitope Results in Positive Selection of Self-Reactive Pathogenic T Cells. The Journal of Immunology. 172(10). 5994–6002. 9 indexed citations
9.
Winkler, Johannes, et al.. (2004). Antibodies generated by a novel DNA vaccination identify the MHC class III encoded BAT2 polypeptide. Vaccine. 23(19). 2540–2550. 4 indexed citations
10.
Neumann, Jürgen, Anna Maria Eis‐Hübinger, & Norbert Koch. (2003). Herpes Simplex Virus Type 1 Targets the MHC Class II Processing Pathway for Immune Evasion. The Journal of Immunology. 171(6). 3075–3083. 85 indexed citations
11.
Sievers, Elisabeth, Jürgen Neumann, Martin Raftery, et al.. (2002). Glycoprotein B from strain 17 of herpes simplex virus type I contains an invariant chain homologous sequence that binds to MHC class II molecules. Immunology. 107(1). 129–135. 26 indexed citations
12.
Neumann, Jürgen, et al.. (2001). Glycosylation Signals That Separate the Trimerization from the MHC Class II-binding Domain Control Intracellular Degradation of Invariant Chain. Journal of Biological Chemistry. 276(16). 13469–13475. 17 indexed citations
13.
Kanzler, Holger, et al.. (2000). Thyroglobulin type‐I‐like domains in invariant chain fusion proteins mediate resistance to cathepsin L digestion. FEBS Letters. 485(1). 67–70. 7 indexed citations
14.
Koch, Norbert, Ian R. van Driel, & Paul A. Gleeson. (2000). Hijacking a chaperone: manipulation of the MHC class II presentation pathway. Immunology Today. 21(11). 546–550. 17 indexed citations
15.
Grüneberg, Ulrike, et al.. (1999). Sodium Dodecyl Sulfate-Resistant HLA-DR “Superdimer” Bands Are in Some Cases Class II Heterodimers Bound to Antibody. The Journal of Immunology. 162(8). 4671–4676. 12 indexed citations
16.
Koch, Norbert, et al.. (1997). Exon 6 Is Essential for Invariant Chain Trimerization and Induction of Large Endosomal Structures. Journal of Biological Chemistry. 272(13). 8281–8287. 36 indexed citations
17.
Koch, Norbert, et al.. (1996). The invariant chain derived fragment CLIP is an efficient in vitro inhibitor of peptide binding to MHC class II molecules. Molecular Immunology. 33(1). 25–31. 3 indexed citations
18.
Koch, Norbert & Brigitta Stockinger. (1991). Molecules that modify antigen recognition. Current Opinion in Immunology. 3(1). 10–15. 3 indexed citations
19.
Bertolino, Patrick, et al.. (1991). Correlation between invariant chain expression level and capability to present antigen to MHC class II-restricted T cells. International Immunology. 3(5). 435–443. 26 indexed citations
20.
Pessara, Ulrich, Frank Momburg, & Norbert Koch. (1988). Cooperative effect of interferon‐γ and tumor necrosis factor‐α on the induction of the class II antigen‐associated invariant chain expression. European Journal of Immunology. 18(11). 1719–1726. 14 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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