Mika Shigematsu

158.4k citations
39 papers · 1.1k indexed · h-index 17

Mika Shigematsu

38 papers receiving 1.1k citations

Peers

Mika Shigematsu
Comparison fields: 5 of 127
  • Modeling and Simulation 98
  • Infectious Diseases 268
  • Endocrinology 72
  • Epidemiology 487
  • Parasitology 80
Replace Roberto Vivancos with:
Roberto Vivancos United Kingdom
Obaghe Edeghere United Kingdom
Kiyosu Taniguchi Japan
César Cabezas Peru
Simon Pollett United States
Julie A. Pavlin United States
I‐Ching Sam Malaysia
Radhika Gharpure United States
D Coulombier Sweden
Paul M. Arguin United States
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Citations per field
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Citations per year

Countries citing papers authored by Mika Shigematsu

Since Specialization
Citations

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

Fields of papers citing papers by Mika Shigematsu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

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

All Works

20 of 20 papers shown
#Work
1 202140
2 2015233
3 20147
4 20142
5 20145
6 20122
7 20111
8 200923
9 200815
10 200821
11 20074
12 200740
13 200739
14 20072
15 200714
16 200719
17
The Development of a Schema for the Annotation of Terms in the Biocaster Disease Detecting/Tracking System.
200612
18
Experimental surveillance using data on sales of over-the-counter medications--Japan, November 2003-April 2004.
200531
19 200187
20 199831

About Mika Shigematsu

Mika Shigematsu is a scholar working on Endocrinology, Modeling and Simulation and Parasitology, having authored 39 papers that have together received 1.1k indexed citations. Recurring topics across this work include Influenza Virus Research Studies (11 papers), Data-Driven Disease Surveillance (11 papers), Respiratory viral infections research (5 papers), Salmonella and Campylobacter epidemiology (5 papers), Biomedical Text Mining and Ontologies (5 papers), Animal Disease Management and Epidemiology (4 papers), Zoonotic diseases and public health (4 papers) and Vibrio bacteria research studies (3 papers). The work is most often cited by research in Modeling and Simulation (98 citations), Infectious Diseases (268 citations) and Endocrinology (72 citations). Mika Shigematsu has collaborated with scholars based in Japan, United Kingdom and United States. Frequent co-authors include Kiyosu Taniguchi, Mike Conway, Nigel Collier, Ai Kawazoe, Elizabeth M. Johnson, Barry Evans, Theresa Lamagni, Laura C. Streichert, Courtney D. Corley and Eric H. Y. Lau. Their work appears in journals such as Bioinformatics, PLoS ONE and The Journal of Infectious Diseases.

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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