Peter Halfmann

17.3k citations
97 papers · 5.7k indexed · 7 hit papers · h-index 35

Peter Halfmann

89 papers receiving 5.6k citations

Hit Papers

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Peers

Peter Halfmann
Comparison fields: 5 of 134
  • Infectious Diseases 3.5k
  • Agronomy and Crop Science 1.0k
  • Epidemiology 3.0k
  • Immunology 1.1k
  • Modeling and Simulation 229
Replace Darwyn Kobasa with:
Darwyn Kobasa Canada
Kyoko Shinya Japan
Jessica A. Belser United States
Shinji Watanabe Japan
John C. Kash United States
Ted M. Ross United States
Maki Kiso Japan
Wenbo Xu China
Young Ki Choi South Korea
Peter Halfmann relative to Darwyn Kobasa Canada Darwyn Kobasa's profile →
Citations per field
00.5×2.8×
Darwyn Kobasa · 1×
Citations per year

Countries citing papers authored by Peter Halfmann

Since Specialization
Citations

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

Fields of papers citing papers by Peter Halfmann

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 20251
2 20255
3 202412
4 20246
5 202312
6 20231
7 20230
8 20230
9 202223
10 202243
11 202132
12 202162
13 202138
14 20213
15 202110
16 202153
17 202023
18 201912
19 2016127
20
EBOVゲノムの転写および複製を阻害するエボラウイルス(EBOV)VP24
20072

About Peter Halfmann

Peter Halfmann is a scholar working on Infectious Diseases, Modeling and Simulation, Epidemiology, Animal Science and Zoology and Agronomy and Crop Science, having authored 97 papers that have together received 5.7k indexed citations. Recurring topics across this work include SARS-CoV-2 and COVID-19 Research (46 papers), Viral Infections and Outbreaks Research (32 papers), Viral Infections and Vectors (20 papers), Influenza Virus Research Studies (19 papers), Viral gastroenteritis research and epidemiology (17 papers), Hepatitis B Virus Studies (15 papers), Respiratory viral infections research (14 papers) and COVID-19 Clinical Research Studies (14 papers). The work is most often cited by research in Infectious Diseases (3.5k citations), Agronomy and Crop Science (1.0k citations), Epidemiology (3.0k citations), Immunology (1.1k citations) and Modeling and Simulation (229 citations). Peter Halfmann has collaborated with scholars based in United States, Japan and Canada. Frequent co-authors include Yoshihiro Kawaoka, Masato Hatta, Peng Gao, Gabriele Neumann, Shinji Watanabe, Takeshi Noda, Heinz Feldmann, Asuka Nanbo, Jinhyun Kim and Kyoko Shinya. Their work appears in journals such as The Journal of Infectious Diseases, Journal of Virology, EBioMedicine, PLoS Pathogens and Nature Communications.

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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