Mika Kishida

459 citations
9 papers · 387 · h-index 8

Impact in

    • Adipokines, Inflammation, and Metabolic Diseases
    • Atherosclerosis and Cardiovascular Diseases
    • Biomarkers in Disease Mechanisms

Papers in

    • Adipokines, Inflammation, and Metabolic Diseases 3
    • Neuroendocrine Tumor Research Advances 2
    • Lipoproteins and Cardiovascular Health 3
    • Cholesterol and Lipid Metabolism 1

Mika Kishida

9 papers receiving 377 citations

Peers

Mika Kishida
Comparison fields: 5 of 60
  • Epidemiology 202
  • Immunology 86
  • Endocrine and Autonomic Systems 27
  • Physiology 103
  • Cardiology and Cardiovascular Medicine 75
Replace R. Temaru with:
R. Temaru Japan
Atsuko Tomizawa Japan
Jorge Plutzky United States
Yonghee Lee South Korea
José C. Sandoval Japan
Rajesh K. Davda United States
Kenichi Tsujii Japan
A Mühlhöfer Germany
Takashi Shimotomai Japan
Fabio Sanna United Kingdom
Mika Kishida relative to R. Temaru Japan R. Temaru's profile →
Citations per field
00.5×1.5×
R. Temaru · 1×
Citations per year

Countries citing papers authored by Mika Kishida

Since Specialization
Citations

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

Fields of papers citing papers by Mika Kishida

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

9 of 9 papers shown
#Work
1 2005212
2 200550
3 199940
4 200138
5 200216
6 20049
7 20058
8 20078
9 20016

About Mika Kishida

Mika Kishida is a scholar working on Epidemiology, Surgery, Immunology, Molecular Biology and Nephrology, having authored 9 papers that have together received 387 indexed citations. Recurring topics across this work include Atherosclerosis and Cardiovascular Diseases (3 papers), Lipoproteins and Cardiovascular Health (3 papers), Adipokines, Inflammation, and Metabolic Diseases (3 papers), Neuroendocrine Tumor Research Advances (2 papers), Chronic Kidney Disease and Diabetes (1 paper), Neuroblastoma Research and Treatments (1 paper), Cholesterol and Lipid Metabolism (1 paper) and IL-33, ST2, and ILC Pathways (1 paper). The work is most often cited by research in Epidemiology (202 citations), Immunology (86 citations), Endocrine and Autonomic Systems (27 citations), Physiology (103 citations) and Cardiology and Cardiovascular Medicine (75 citations). Mika Kishida has collaborated with scholars based in Japan. Frequent co-authors include Masaharu Urakaze, Masashi Kobayashi, Akira Sato, Katsuya Yamazaki, R. Temaru, Chikaaki Kobashi, Hideki Kobayashi, Shinji Kihara, Norio Nakamura and Tohru Funahashi. Their work appears in journals such as Circulation Research, Annals of Nuclear Medicine, Respirology, Hormone and Metabolic Research and Experimental and Clinical Endocrinology & Diabetes.

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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