Akane Yakushiji
- Artificial Intelligence top 5%
- Molecular Biology
- Information Systems
- Computational Theory and Mathematics
- Management Science and Operations Research
- Co-authors
- Yuka TateisiJun’ichi TsujiiYusuke MiyaoTomoko OhtaJin-Dong KimYoshimasa TsuruokaJunko S. TakeuchiKazuhiro YOSHIDA
- Topics
- Biomedical Text Mining and Ontologies (7 papers)Natural Language Processing Techniques (7 papers)Semantic Web and Ontologies (5 papers)
- Journals
- Language Resources and EvaluationPubMedMedical Entomology and Zoology
- Partner nations
- JapanUnited Kingdom
In The Last Decade
Akane Yakushiji
9 papers receiving 282 citations
Peers
Comparison fields: 5 of 26
- Artificial Intelligence 250
- Molecular Biology 237
- Information Systems 12
- Computational Theory and Mathematics 11
- Management Science and Operations Research 5
Countries citing papers authored by Akane Yakushiji
This map shows the geographic impact of Akane Yakushiji'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 Akane Yakushiji with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Akane Yakushiji more than expected).
Fields of papers citing papers by Akane Yakushiji
This network shows the impact of papers produced by Akane Yakushiji. 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 Akane Yakushiji. The network helps show where Akane Yakushiji may publish in the future.
Co-authorship network of co-authors of Akane Yakushiji
This figure shows the co-authorship network connecting the top 25 collaborators of Akane Yakushiji. A scholar is included among the top collaborators of Akane Yakushiji 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 Akane Yakushiji. Akane Yakushiji is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | Linguistic and Biological Annotations of Biological Interaction Events | 3 |
| 2 | 25 | |
| 3 | 20 | |
| 4 | Biomedical information extraction with predicate-argument structure patterns | 1 |
| 5 | Syntax Annotation for the GENIA Corpus | 91 |
| 6 | 0 | |
| 7 | 2 | |
| 8 | 149 | |
| 9 | 6 | |
| 10 | 4 |
About Akane Yakushiji
Akane Yakushiji is a scholar working on Artificial Intelligence, Molecular Biology and Infectious Diseases, having authored 10 papers that have together received 301 indexed citations. Recurring topics across this work include Biomedical Text Mining and Ontologies (7 papers), Natural Language Processing Techniques (7 papers) and Semantic Web and Ontologies (5 papers). The work is most often cited by research in Artificial Intelligence (250 citations), Molecular Biology (237 citations) and Health Informatics (2 citations). Akane Yakushiji has collaborated with scholars based in Japan and United Kingdom. Frequent co-authors include Yuka Tateisi, Jun’ichi Tsujii, Yusuke Miyao, Tomoko Ohta, Jin-Dong Kim, Yoshimasa Tsuruoka, Junko S. Takeuchi, Kazuhiro YOSHIDA, Jun'ichi Tsujii and Takashi Ninomiya. Their work appears in journals such as Language Resources and Evaluation, PubMed and Medical Entomology and Zoology.
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.