Raphael N. Sieber

2.5k citations
29 papers · 804 · h-index 13

Impact in

Papers in

    • Antimicrobial Resistance in Staphylococcus 14
    • SARS-CoV-2 and COVID-19 Research 6
    • Clostridium difficile and Clostridium perfringens research 3
    • Bacterial biofilms and quorum sensing 5

Raphael N. Sieber

28 papers receiving 792 citations

Peers

Raphael N. Sieber
Comparison fields: 5 of 82
  • Infectious Diseases 567
  • Modeling and Simulation 91
  • Clinical Biochemistry 106
  • Health 96
  • Microbiology 70
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Citations per year

Countries citing papers authored by Raphael N. Sieber

Since Specialization
Citations

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

Fields of papers citing papers by Raphael N. Sieber

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Raphael N. Sieber. 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 Raphael N. Sieber. The network helps show where Raphael N. Sieber may publish in the future.

Co-authors

The 25 scholars most cited alongside Raphael N. Sieber, 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 Raphael N. Sieber Line = papers co-authored together Raphael N. Sieber links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 29 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2011102
2 202299
3 202283
4 201773
5 201871
6 202269
7 201752
8 201945
9 201933
10 201931
11 202228
12 202022
13 202013
14 202111
15 202311
16 202011
17 20238
18 20207
19 20206
20 20206

About Raphael N. Sieber

Raphael N. Sieber is a scholar working on Infectious Diseases, Molecular Biology, Epidemiology, Ecology and Microbiology, having authored 29 papers that have together received 804 indexed citations. Recurring topics across this work include Antimicrobial Resistance in Staphylococcus (14 papers), Mycobacterium research and diagnosis (6 papers), SARS-CoV-2 and COVID-19 Research (6 papers), Bacterial biofilms and quorum sensing (5 papers), Bacteriophages and microbial interactions (4 papers), Microbial infections and disease research (4 papers), Bacterial Identification and Susceptibility Testing (3 papers) and Clostridium difficile and Clostridium perfringens research (3 papers). The work is most often cited by research in Infectious Diseases (567 citations), Modeling and Simulation (91 citations), Clinical Biochemistry (106 citations), Health (96 citations) and Microbiology (70 citations). Raphael N. Sieber has collaborated with scholars based in Denmark, United States and United Kingdom. Frequent co-authors include Marc Stegger, Robert Skov, Jesper Larsen, Anders Rhod Larsen, Christoph Vorburger, Yannick‐Serge Zimmermann, Camilla Holten Møller, Morten Rasmussen, Lance B. Price and Jannik Fonager. Their work appears in journals such as Frontiers in Microbiology, Nature Communications, Applied and Environmental Microbiology, Journal of Antimicrobial Chemotherapy and Scientific Reports.

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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