Mai Okada

813 citations
22 papers · 648 · h-index 13

Impact in

Papers in

    • Glycosylation and Glycoproteins Research 3
    • Pluripotent Stem Cells Research 3
    • Protein Structure and Dynamics 3
    • Protein purification and stability 2
    • Viral Infectious Diseases and Gene Expression in Insects 2
    • Coagulation, Bradykinin, Polyphosphates, and Angioedema 2

Mai Okada

22 papers receiving 644 citations

Peers

Mai Okada
Comparison fields: 5 of 97
  • Physical and Theoretical Chemistry 99
  • Biophysics 56
  • Genetics 68
  • Toxicology 20
  • Molecular Biology 316
Replace Takayoshi Watanabe with:
Takayoshi Watanabe Japan
Elisabetta Galbiati Italy
Alok Dube India
Philippe Mellet France
Louis Cincotta United States
Ekaterina Yu. Rybalkina Russia
J. PARRICK United Kingdom
Yonghao Li China
Maria Paravatou‐Petsotas Greece
Binbin Ma China
Mai Okada relative to Takayoshi Watanabe Japan Takayoshi Watanabe's profile →
Citations per field
00.5×6.2×
Takayoshi Watanabe · 1×
Citations per year

Countries citing papers authored by Mai Okada

Since Specialization
Citations

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

Fields of papers citing papers by Mai Okada

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 22 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2002113
2 2014103
3 200164
4 201656
5 201446
6 201737
7 201136
8 201335
9 200230
10 201127
11 201422
12 201815
13 200914
14 202112
15 20238
16 20217
17 20196
18 20205
19 20145
20
Cell therapy for facial anti-aging.
20085

About Mai Okada

Mai Okada is a scholar working on Molecular Biology, Genetics, Biomedical Engineering, Radiology, Nuclear Medicine and Imaging and Atomic and Molecular Physics, and Optics, having authored 22 papers that have together received 648 indexed citations. Recurring topics across this work include 3D Printing in Biomedical Research (4 papers), Glycosylation and Glycoproteins Research (3 papers), Pluripotent Stem Cells Research (3 papers), Protein Structure and Dynamics (3 papers), Monoclonal and Polyclonal Antibodies Research (3 papers), Coagulation, Bradykinin, Polyphosphates, and Angioedema (2 papers), Protein purification and stability (2 papers) and Viral Infectious Diseases and Gene Expression in Insects (2 papers). The work is most often cited by research in Physical and Theoretical Chemistry (99 citations), Biophysics (56 citations), Genetics (68 citations), Toxicology (20 citations) and Molecular Biology (316 citations). Mai Okada has collaborated with scholars based in Japan, United States and Malaysia. Frequent co-authors include Michio Iwaoka, Shuji Tomoda, Kei Motomura, Takeshi Ikeda, Akio Kuroda, Ryuichi Hirota, Ryuji Kato, Hiroyuki Honda, Takenori Ishida and Kei Kanie. Their work appears in journals such as Theriogenology, Scientific Reports, Biochemical and Biophysical Research Communications, PLoS ONE and Journal of Materials Science.

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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