Oliver Ratmann

53 papers receiving 1.6k citations

Peers

Oliver Ratmann
Comparison fields: 5 of 135
  • Virology 196
  • Modeling and Simulation 147
  • Developmental Biology 61
  • Infectious Diseases 372
  • Statistics and Probability 104
Replace Eduardo A. Undurraga with:
Eduardo A. Undurraga Chile
Fraser Lewis Switzerland
Jonathan C. Marshall New Zealand
Pratha Sah United States
Marc Choisy France
Stephen Q. Muth United States
John J. Potterat United States
Guangjian Zhu China
Robin N. Thompson United Kingdom
Paula M. Luz Brazil
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Citations per field
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Eduardo A. Undurraga · 1×
Citations per year

Countries citing papers authored by Oliver Ratmann

Since Specialization
Citations

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

Fields of papers citing papers by Oliver Ratmann

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 57 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2021154
2 2021136
3 2017135
4 201197
5 201689
6 201888
7 201786
8 201585
9 200984
10 202366
11 200765
12 202158
13 201252
14 202248
15 201142
16 202141
17 201527
18 202127
19 201227
20 200925

About Oliver Ratmann

Oliver Ratmann is a scholar working on Epidemiology, Infectious Diseases, Virology, Molecular Biology and Modeling and Simulation, having authored 57 papers that have together received 1.6k indexed citations. Recurring topics across this work include HIV Research and Treatment (14 papers), HIV/AIDS Research and Interventions (10 papers), COVID-19 epidemiological studies (8 papers), HIV, Drug Use, Sexual Risk (7 papers), Influenza Virus Research Studies (6 papers), Genomics and Phylogenetic Studies (6 papers), Bioinformatics and Genomic Networks (5 papers) and Protein Structure and Dynamics (4 papers). The work is most often cited by research in Virology (196 citations), Modeling and Simulation (147 citations), Developmental Biology (61 citations), Infectious Diseases (372 citations) and Statistics and Probability (104 citations). Oliver Ratmann has collaborated with scholars based in United Kingdom, United States and Denmark. Frequent co-authors include Katia Koelle, Maciej F. Boni, Ha Minh Lam, Carsten Wiuf, Christophe Fraser, Seth Flaxman, David A. Rasmussen, Sylvia Richardson, H. Juliette T. Unwin and Stephen Nowicki. Their work appears in journals such as PLoS Computational Biology, The Lancet, Proceedings of the National Academy of Sciences, The Journal of Infectious Diseases and Proceedings of the Royal Society B Biological Sciences.

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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