Caroline S. Brown

2.1k citations
13 papers · 1.5k indexed · 1 hit paper · h-index 10
Topics
Influenza Virus Research Studies (6 papers)Parvovirus B19 Infection Studies (6 papers)COVID-19 epidemiological studies (5 papers)

In The Last Decade

Caroline S. Brown

13 papers receiving 1.4k citations

Hit Papers

Commentary: Middle East Respiratory Syndrome Coronavirus ...20132026201720212013250500750

Peers

Caroline S. Brown
Comparison fields: 5 of 128
  • Infectious Diseases 985
  • Epidemiology 312
  • Animal Science and Zoology 233
  • Modeling and Simulation 172
  • Molecular Biology 143
Replace Bone S. F. Tang with:
Bone S. F. Tang Hong Kong
Ali S. Omrani Saudi Arabia
Mike Catton Australia
Xingguang Li China
Abdullah A Al-Rabeeah Saudi Arabia
Abualgasim Elgaili Abdalla Saudi Arabia
Shirin Kalimuddin Singapore
Reed F. Johnson United States
Yi Xu China
Marilda Mendonça Siqueira Brazil
Caroline S. Brown relative to Bone S. F. Tang Hong Kong Bone S. F. Tang's profile →
Citations per field
00.5×1.5×1.8×
Bone S. F. Tang · 1×
Citations per year

Countries citing papers authored by Caroline S. Brown

Since Specialization
Citations

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

Fields of papers citing papers by Caroline S. Brown

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Caroline S. Brown. 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 Caroline S. Brown. The network helps show where Caroline S. Brown may publish in the future.

Co-authorship network of co-authors of Caroline S. Brown

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

All Works

13 of 13 papers shown
#WorkIndexed citations
1 107
2 208
3 6
4
Commentary: Middle East Respiratory Syndrome Coronavirus (MERS-CoV): Announcement of the Coronavirus Study Groupbreakdown →
917
5 7
6 11
7 17
8 6
9 26
10 37
11 42
12 38
13 62

About Caroline S. Brown

Caroline S. Brown is a scholar working on Modeling and Simulation, Infectious Diseases and Hematology, having authored 13 papers that have together received 1.5k indexed citations. Recurring topics across this work include Influenza Virus Research Studies (6 papers), Parvovirus B19 Infection Studies (6 papers) and COVID-19 epidemiological studies (5 papers). The work is most often cited by research in Infectious Diseases (985 citations), Modeling and Simulation (172 citations) and Animal Science and Zoology (233 citations). Caroline S. Brown has collaborated with scholars based in Netherlands, Denmark and United Kingdom. Frequent co-authors include Alexander E. Gorbalenya, Leo L. M. Poon, Christian Drosten, Mónica Galiano, Luis Enjuanes, Ali M. Zaki, Raoul J. de Groot, Eric J. Snijder, John Ziebuhr and Ron A. M. Fouchier. Their work appears in journals such as Journal of Virology, Virology and Vaccine.

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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