Asako Koike

3.5k citations
34 papers · 567 · h-index 15

Impact in

Papers in

    • Bioinformatics and Genomic Networks 10
    • Biomedical Text Mining and Ontologies 6
    • Genomics and Phylogenetic Studies 5
    • Machine Learning in Bioinformatics 4
    • Genetic Associations and Epidemiology 5

Asako Koike

34 papers receiving 541 citations

Peers

Asako Koike
Comparison fields: 5 of 97
  • Genetics 135
  • Ophthalmology 41
  • Molecular Biology 310
  • Cancer Research 52
  • Artificial Intelligence 98
Replace Yihao Liu with:
Yihao Liu China
Rui Cheng China
Mahmut Şamil Sağıroğlu Türkiye
Felipe Giuste United States
Hyun-Hwan Jeong United States
Taibo Li United States
Richard Rivera Ecuador
Kaur Alasoo Estonia
Weizhi Zhang China
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Citations per field
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Yihao Liu · 1×
Citations per year

Countries citing papers authored by Asako Koike

Since Specialization
Citations

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

Fields of papers citing papers by Asako Koike

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 34 papers — load more, or switch the sort, to bring in the rest.

#Work
1 201467
2 200455
3 200349
4 200846
5 201145
6 199835
7 200830
8 199430
9
Gene/Protein/Family Name Recognition in Biomedical Literature
200426
10 201026
11 201526
12 200622
13 200919
14 199918
15 201116
16
PRIME: automatically extracted PRotein Interactions and Molecular Information databasE.
20059
17 20158
18 20095
19 19985
20 20034

About Asako Koike

Asako Koike is a scholar working on Molecular Biology, Genetics, Artificial Intelligence, Atomic and Molecular Physics, and Optics and Computational Theory and Mathematics, having authored 34 papers that have together received 567 indexed citations. Recurring topics across this work include Bioinformatics and Genomic Networks (10 papers), Biomedical Text Mining and Ontologies (6 papers), Genomics and Phylogenetic Studies (5 papers), Genetic Associations and Epidemiology (5 papers), Algorithms and Data Compression (5 papers), Machine Learning in Bioinformatics (4 papers), Computational Drug Discovery Methods (3 papers) and Force Microscopy Techniques and Applications (3 papers). The work is most often cited by research in Genetics (135 citations), Ophthalmology (41 citations), Molecular Biology (310 citations), Cancer Research (52 citations) and Artificial Intelligence (98 citations). Asako Koike has collaborated with scholars based in Japan, South Korea and United States. Frequent co-authors include Toshihisa Takagi, Makiko Yoshida, Nao Nishida, Katsushi Tokunaga, Makoto Yoneya, Yoshiki Niwa, Yoshiyuki Kobayashi, Kouichi Kimura, Ituro Inoue and Shoji Tsuji. Their work appears in journals such as Proceedings Genome Informatics Workshop/Genome informatics, Alzheimer s & Dementia, Bioinformatics, BMC Bioinformatics and The Journal of Physical Chemistry B.

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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