Jan Münch

15.6k total citations · 2 hit papers
182 papers, 7.3k citations indexed

About

Jan Münch is a scholar working on Virology, Infectious Diseases and Immunology. According to data from OpenAlex, Jan Münch has authored 182 papers receiving a total of 7.3k indexed citations (citations by other indexed papers that have themselves been cited), including 74 papers in Virology, 73 papers in Infectious Diseases and 60 papers in Immunology. Recurrent topics in Jan Münch's work include HIV Research and Treatment (74 papers), Immune Cell Function and Interaction (30 papers) and HIV/AIDS drug development and treatment (29 papers). Jan Münch is often cited by papers focused on HIV Research and Treatment (74 papers), Immune Cell Function and Interaction (30 papers) and HIV/AIDS drug development and treatment (29 papers). Jan Münch collaborates with scholars based in Germany, United States and France. Jan Münch's co-authors include Frank Kirchhoff, Michael Schindler, Janis A. Müller, Stefan Pöhlmann, Rüdiger Groß, Nadia R. Roan, Onofrio Zirafi, Warner C. Greene, Ludger Ständker and Carina Conzelmann and has published in prestigious journals such as Nature, Cell and Proceedings of the National Academy of Sciences.

In The Last Decade

Jan Münch

177 papers receiving 7.2k citations

Hit Papers

SARS-CoV-2 variants B.1.351... 2011 2026 2016 2021 2021 2011 100 200 300 400 500

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Jan Münch Germany 45 2.8k 2.6k 2.3k 2.0k 1.4k 182 7.3k
Mario Ostrowski Canada 51 3.2k 1.2× 1.9k 0.7× 1.5k 0.7× 3.4k 1.7× 1.3k 0.9× 134 7.3k
Manfred P. Dierich Austria 49 1.7k 0.6× 2.3k 0.9× 1.3k 0.6× 3.3k 1.7× 1.6k 1.1× 221 7.6k
Michel J. Tremblay Canada 52 3.4k 1.2× 1.5k 0.6× 2.5k 1.1× 3.5k 1.8× 2.0k 1.4× 238 9.3k
David M. Markovitz United States 45 2.4k 0.9× 1.5k 0.6× 3.1k 1.4× 2.2k 1.1× 1.2k 0.8× 119 7.5k
Luis J. Montaner United States 46 3.1k 1.1× 2.1k 0.8× 1.1k 0.5× 3.7k 1.9× 1.3k 0.9× 190 6.9k
Robin J. Shattock United Kingdom 54 4.6k 1.7× 4.1k 1.6× 3.1k 1.4× 3.3k 1.7× 2.5k 1.7× 273 11.1k
Julia A. Metcalf United States 50 5.9k 2.1× 4.0k 1.5× 1.4k 0.6× 4.4k 2.2× 1.9k 1.3× 103 9.9k
José Alcamı́ Spain 48 2.8k 1.0× 1.7k 0.7× 2.4k 1.0× 2.4k 1.2× 1.1k 0.7× 211 6.9k
Roger J. Pomerantz United States 55 7.2k 2.6× 4.7k 1.8× 3.2k 1.4× 2.8k 1.4× 2.8k 1.9× 207 11.5k
Hui Zhang China 50 2.6k 1.0× 2.3k 0.9× 4.8k 2.1× 2.8k 1.4× 1.9k 1.3× 276 10.2k

Countries citing papers authored by Jan Münch

Since Specialization
Citations

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

Fields of papers citing papers by Jan Münch

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Jan Münch

This figure shows the co-authorship network connecting the top 25 collaborators of Jan Münch. A scholar is included among the top collaborators of Jan Münch 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 Jan Münch. Jan Münch 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
2.
Hayn, Manuel, et al.. (2024). Hybrid Materials From Peptide Nanofibrils and Magnetic Beads to Concentrate and Isolate Virus Particles. Advanced Functional Materials. 34(27). 3 indexed citations
3.
Batista, Alex D., et al.. (2024). Rational design based on multi-monomer simultaneous docking for epitope imprinting of SARS-CoV-2 spike protein. Scientific Reports. 14(1). 23057–23057. 6 indexed citations
4.
Rodríguez, Armando, Ludger Ständker, Mirja Harms, et al.. (2024). An Optimized Peptide Antagonist of CXCR4 Limits Survival of BCR–ABL1-Transformed Cells in Philadelphia-Chromosome-Positive B-Cell Acute Lymphoblastic Leukemia. International Journal of Molecular Sciences. 25(15). 8306–8306. 2 indexed citations
5.
Synatschke, Christopher V., et al.. (2023). Inverse design of viral infectivity-enhancing peptide fibrils from continuous protein-vector embeddings. Biomaterials Science. 11(15). 5251–5261. 14 indexed citations
6.
Rodríguez, Armando, Annia Alba, Antonio A. Vázquez, et al.. (2023). Identification and Characterization of Three New Antimicrobial Peptides from the Marine Mollusk Nerita versicolor (Gmelin, 1791). International Journal of Molecular Sciences. 24(4). 3852–3852. 15 indexed citations
7.
Schütz, Desirée, et al.. (2023). Cryo-EM structure and polymorphic maturation of a viral transduction enhancing amyloid fibril. Nature Communications. 14(1). 4293–4293. 7 indexed citations
8.
Harms, Mirja, Rüdiger Groß, Benjamin Mayer, et al.. (2022). Utilization of Aminoguanidine Prevents Cytotoxic Effects of Semen. International Journal of Molecular Sciences. 23(15). 8563–8563. 1 indexed citations
10.
Ruiz‐Blanco, Yasser B., Joel Mieres‐Pérez, Mirja Harms, et al.. (2022). PPI-Affinity: A Web Tool for the Prediction and Optimization of Protein–Peptide and Protein–Protein Binding Affinity. Journal of Proteome Research. 21(8). 1829–1841. 49 indexed citations
11.
Zech, Fabian, Tatjana Weil, Alina Seidel, et al.. (2022). Severe Acute Respiratory Syndrome Coronavirus 2 Vaccination Boosts Neutralizing Activity Against Seasonal Human Coronaviruses. Clinical Infectious Diseases. 75(1). e653–e661. 14 indexed citations
13.
Wettstein, Lukas, Christian Kersten, Tatjana Weil, et al.. (2022). Peptidomimetic inhibitors of TMPRSS2 block SARS-CoV-2 infection in cell culture. Communications Biology. 5(1). 681–681. 17 indexed citations
14.
Hayn, Manuel, Armando Rodríguez, Solange Vidal, et al.. (2021). Natural cystatin C fragments inhibit GPR15-mediated HIV and SIV infection without interfering with GPR15L signaling. Proceedings of the National Academy of Sciences. 118(3). 12 indexed citations
15.
Wettstein, Lukas, Elad Arad, Ashim Paul, et al.. (2021). Dual concentration-dependent effect of ascorbic acid on PAP(248–286) amyloid formation and SEVI-mediated HIV infection. RSC Chemical Biology. 2(5). 1534–1545. 1 indexed citations
16.
Fresco‐Cala, Beatriz, et al.. (2021). Development and Characterization of Magnetic SARS-CoV-2 Peptide-Imprinted Polymers. Nanomaterials. 11(11). 2985–2985. 12 indexed citations
17.
Harms, Mirja, Andrea Gilg, Ludger Ständker, et al.. (2020). Microtiter plate-based antibody-competition assay to determine binding affinities and plasma/blood stability of CXCR4 ligands. Scientific Reports. 10(1). 16 indexed citations
18.
Kumar, Vipin, Carina Conzelmann, Nikaïa Smith, et al.. (2019). Nucleic Acids as a Nature‐Inspired Scaffold for Macromolecular Prodrugs of Nucleoside Analogues. Advanced Science. 6(6). 1802095–1802095. 5 indexed citations
19.
Frich, Camilla Kaas, Raoul Walther, Frederik Dagnæs‐Hansen, et al.. (2018). Non-covalent hitchhiking on endogenous carriers as a protraction mechanism for antiviral macromolecular prodrugs. Journal of Controlled Release. 294. 298–310. 17 indexed citations
20.
Frich, Camilla Kaas, Annika Röcker, Janis A. Müller, et al.. (2017). Macromolecular Antiviral Agents against Zika, Ebola, SARS, and Other Pathogenic Viruses. Advanced Healthcare Materials. 6(23). 47 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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