Keiko Miwa

4.0k citations
46 papers · 3.2k indexed · 1 hit paper · h-index 24
Topics
Tissue Engineering and Regenerative Medicine (10 papers)Digital Imaging for Blood Diseases (5 papers)Neuroscience and Neural Engineering (5 papers)

In The Last Decade

Keiko Miwa

44 papers receiving 3.2k citations

Hit Papers

Identification of a factor that links apoptotic cells to ...200220262010201820022505007501000

Peers

Keiko Miwa
Comparison fields: 5 of 114
  • Immunology 1.9k
  • Molecular Biology 1.3k
  • Physiology 569
  • Surgery 322
  • Biomedical Engineering 180
Replace Xunrong Luo with:
Xunrong Luo United States
Thomas E. Ichim United States
Tatyana Chernova United Kingdom
Per Anderson Spain
Carmelo Mavilia Italy
Satoshi Serada Japan
Herbert Schwarz Singapore
Yuti Chernajovsky United Kingdom
Carole A. Oskeritzian United States
Zu‐Xi Yu United States
Keiko Miwa relative to Xunrong Luo United States Xunrong Luo's profile →
Citations per field
00.5×2.6×
Xunrong Luo · 1×
Citations per year

Countries citing papers authored by Keiko Miwa

Since Specialization
Citations

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

Fields of papers citing papers by Keiko Miwa

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Keiko Miwa

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

All Works

20 of 20 papers shown
#WorkIndexed citations
1 0
2 12
3 4
4 11
5 40
6 55
7 50
8 7
9 17
10 37
11 24
12 103
13 222
14 0
15 57
16 1
17
Identification of a factor that links apoptotic cells to phagocytesbreakdown →
1110
18 15
19 79
20 84

About Keiko Miwa

Keiko Miwa is a scholar working on Immunology, Biological Psychiatry and Cellular and Molecular Neuroscience, having authored 46 papers that have together received 3.2k indexed citations. Recurring topics across this work include Tissue Engineering and Regenerative Medicine (10 papers), Digital Imaging for Blood Diseases (5 papers) and Neuroscience and Neural Engineering (5 papers). The work is most often cited by research in Immunology (1.9k citations), Immunology and Allergy (139 citations) and Physiology (569 citations). Keiko Miwa has collaborated with scholars based in Japan, Netherlands and United States. Frequent co-authors include Shigekazu Nagata, Rikinari Hanayama, Masato Tanaka, Akihiro Iwamatsu, Azusa Shinohara, Takashi Suda, Masahide Asano, Yoichiro Iwakura, Reiko Horai and Kohki Kawane. Their work appears in journals such as Nature, Journal of Biological Chemistry and Nature Medicine.

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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