Peter V. Markov

1.4k citations
5 papers · 622 indexed · 1 hit paper · h-index 2
Topics
SARS-CoV-2 and COVID-19 Research (3 papers)vaccines and immunoinformatics approaches (1 paper)Bacillus and Francisella bacterial research (1 paper)

In The Last Decade

Peter V. Markov

2 papers receiving 613 citations

Hit Papers

The evolution of SARS-CoV-220232026202420252023100200300400500

Peers

Peter V. Markov
Comparison fields: 5 of 95
  • Infectious Diseases 482
  • Molecular Biology 158
  • Modeling and Simulation 87
  • Animal Science and Zoology 63
  • Epidemiology 58
Replace F. Akter with:
F. Akter Bangladesh
Brent Oosthuysen South Africa
Michael T. Boswell South Africa
Veronica Ueckermann South Africa
Frances Ayres South Africa
Juanita Pang United Kingdom
Claire Carlin United States
Hans C. Leier United States
Karin van den Berg South Africa
Bojan F. Hörnich Germany
Peter V. Markov relative to F. Akter Bangladesh F. Akter's profile →
Citations per field
00.5×5.3×
F. Akter · 1×
Citations per year

Countries citing papers authored by Peter V. Markov

Since Specialization
Citations

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

Fields of papers citing papers by Peter V. Markov

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Peter V. Markov

This figure shows the co-authorship network connecting the top 25 collaborators of Peter V. Markov. A scholar is included among the top collaborators of Peter V. Markov 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 Peter V. Markov. Peter V. Markov is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

About Peter V. Markov

Peter V. Markov is a scholar working on Modeling and Simulation, Infectious Diseases and Agronomy and Crop Science, having authored 5 papers that have together received 622 indexed citations. Recurring topics across this work include SARS-CoV-2 and COVID-19 Research (3 papers), vaccines and immunoinformatics approaches (1 paper) and Bacillus and Francisella bacterial research (1 paper). The work is most often cited by research in Infectious Diseases (482 citations), Modeling and Simulation (87 citations) and Animal Science and Zoology (63 citations). Peter V. Markov has collaborated with scholars based in Italy, United Kingdom and Germany. Frequent co-authors include Aris Katzourakis, Nikolaos I. Stilianakis, Katrina Lythgoe, Peter Simmonds, Martin Beer, Mahan Ghafari, Sergio Consoli, Pietro Coletti, Christos Hadjichristodoulou and Ioannis Kioutsioukis. Their work appears in journals such as Nature Reviews Microbiology, Scientific Reports and Journal of The Royal Society Interface.

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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