Akika Ejima

488 citations
16 papers · 374 indexed · h-index 12

Impact in

    • Mesenchymal stem cell research
    • Pluripotent Stem Cells Research
    • Protein Hydrolysis and Bioactive Peptides
    • CRISPR and Genetic Engineering
    • Muscle Physiology and Disorders

Papers in

    • Muscle metabolism and nutrition 2
    • Adipose Tissue and Metabolism 3
    • Biochemical effects in animals 2

Akika Ejima

15 papers receiving 370 citations

Peers

Akika Ejima
Comparison fields: 5 of 77
  • Genetics 37
  • Molecular Biology 218
  • Physiology 76
  • Rehabilitation 14
  • Developmental Neuroscience 8
Replace Zhifang Wu with:
Zhifang Wu China
Cristina Velez‐delValle Mexico
Samuele Cheri Italy
Toshio Ariyasu Japan
Behrang Alani Iran
Bojiang Li China
Seung‐Hoon Lee South Korea
Guilian Sun China
Kateřina Štefková Czechia
Zhixu He China
Akika Ejima relative to Zhifang Wu China Zhifang Wu's profile →
Citations per field
00.5×
Zhifang Wu · 1×
Citations per year

Countries citing papers authored by Akika Ejima

Since Specialization
Citations

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

Fields of papers citing papers by Akika Ejima

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

16 of 16 papers shown
#Work
1 201599
2 201550
3 201546
4 201833
5 201327
6 201517
7 202217
8 201415
9 201915
10 201814
11 202013
12 201812
13 20246
14 20196
15 20164
16 20210

About Akika Ejima

Akika Ejima is a scholar working on Cell Biology, Physiology, Virology, Genetics and Biochemistry, having authored 16 papers that have together received 374 indexed citations. Recurring topics across this work include Protein Hydrolysis and Bioactive Peptides (4 papers), Adipose Tissue and Metabolism (3 papers), Mesenchymal stem cell research (2 papers), Bone Tissue Engineering Materials (2 papers), Biochemical effects in animals (2 papers), Muscle metabolism and nutrition (2 papers), Bone Metabolism and Diseases (2 papers) and Pluripotent Stem Cells Research (2 papers). The work is most often cited by research in Genetics (37 citations), Molecular Biology (218 citations), Physiology (76 citations), Rehabilitation (14 citations) and Developmental Neuroscience (8 citations). Akika Ejima has collaborated with scholars based in Japan, United States and Myanmar. Frequent co-authors include Osam Mazda, Tsunao Kishida, Toshiro Yamamoto, Kenji Sato, Kenta Yamamoto, Hiroyoshi Fujiwara, Narisato Kanamura, Toshikazu Kubo, Keisuke Nishioka and Yoshiki Sato. Their work appears in journals such as Biochemical and Biophysical Research Communications, BioMetals, Journal of Photochemistry and Photobiology B Biology, Nature Cell Biology and Journal of the Science of Food and Agriculture.

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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