Robert C. Münch

941 citations
14 papers · 778 · h-index 12

Impact in

  • Genetics top 5%
    • Virus-based gene therapy research
  • Oncology top 10%
    • CAR-T cell therapy research

Papers in

    • Virus-based gene therapy research 12
    • RNA Interference and Gene Delivery 8
    • CRISPR and Genetic Engineering 4
    • Viral Infectious Diseases and Gene Expression in Insects 1

Robert C. Münch

13 papers receiving 769 citations

Peers

Robert C. Münch
Comparison fields: 5 of 51
  • Genetics 505
  • Oncology 237
  • Molecular Biology 500
  • Animal Science and Zoology 60
  • Virology 23
Replace Irene C. Schneider with:
Irene C. Schneider Germany
Geoffrey L. Rogers United States
Dong‐Soo Im South Korea
Taco G. Uil Netherlands
Hongjie Wang United States
Duncan McVey United States
Nicola Philpott United States
Lauren E. Mays United States
Murielle Gantzer France
Dan J. Von Seggern United States
Robert C. Münch relative to Irene C. Schneider Germany Irene C. Schneider's profile →
Citations per field
00.5×1.5×2.3×
Irene C. Schneider · 1×
Citations per year

Countries citing papers authored by Robert C. Münch

Since Specialization
Citations

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

Fields of papers citing papers by Robert C. Münch

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside Robert C. Münch, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Robert C. Münch Line = papers co-authored together Robert C. Münch links everyone, so they are left out of the graph.

All Works

14 of 14 papers shown
#Work
1 2012142
2 2010123
3 2015107
4 201197
5 201363
6 201557
7 201345
8 201745
9 201833
10 201325
11 201621
12 200917
13 20153
14 20210

About Robert C. Münch

Robert C. Münch is a scholar working on Genetics, Molecular Biology, Epidemiology, Animal Science and Zoology and Oncology, having authored 14 papers that have together received 778 indexed citations. Recurring topics across this work include Virus-based gene therapy research (12 papers), RNA Interference and Gene Delivery (8 papers), Virology and Viral Diseases (4 papers), CRISPR and Genetic Engineering (4 papers), CAR-T cell therapy research (2 papers), Animal Virus Infections Studies (2 papers), Cytomegalovirus and herpesvirus research (1 paper) and Viral Infectious Diseases and Gene Expression in Insects (1 paper). The work is most often cited by research in Genetics (505 citations), Oncology (237 citations), Molecular Biology (500 citations), Animal Science and Zoology (60 citations) and Virology (23 citations). Robert C. Münch has collaborated with scholars based in Germany, Switzerland and United States. Frequent co-authors include Christian J. Buchholz, Andreas Plückthun, Hildegard Büning, Klaus Cichutek, Anke Muth, Michael Hallek, Hanna Janicki, Sabrina Kneissl, Irene C. Schneider and Michael D. Mühlebach. Their work appears in journals such as Molecular Therapy, Molecular Therapy — Methods & Clinical Development, Nature Methods, Journal of Virology and The Journal of Immunology.

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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