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Name YAMAGUCHI Atsuko
Official Title Professor
Affiliation Department of Design and Data Science
E-mail atsuko@tcu.ac.jp
Web
  1. https://www.linkedin.com/in/atsukoyamaguchi/
  2. https://www.risys.gl.tcu.ac.jp/Main.php?action=profile&type=detail&selected_lang=E&tchCd=5002156000
Profile I am interested in graph theory, databases, and statistics, and I have applied them to data in the life sciences. I am recently researching knowledge graphs, which are flexible and powerful data models that can integrate data from various sources. With knowledge graphs, it becomes possible to extract essential information from enormous datasets, which have wide-ranging applications across different fields. I am interested in exploring the potential of knowledge graphs.
Research Field(Keyword & Summary)
  1. 1. Knowledge Graph

    A knowledge graph is a type of data model that has a graph-like structure, which allows it to easily combine data from different sources and provide users with multiple ways to search and make use of the information. We are developing systems to make it easier to construct graphs and utilize data presented as knowledge graphs.

  2. 2. Data Integration on Life Sciences using Knowledge Graph

    Advancements in measurement instruments in life sciences have led to the generation of vast and varied datasets, which are being increasingly organized into knowledge graphs worldwide. However, due to the massive size of the original data, resulting in a graph with an enormous number of nodes as a whole. We are exploring ways to extract essential information from these enormous knowledge graphs.

  3. 3. Applications that utilize Data Distributed across the World Wide Web

    The data is often scattered across different services on the web, but when combined and integrated, it can lead to a multitude of applications. We are develpping such applications as softwares and made available as services on the web or open source softwares.
Representative Papers
  1. Advances in the development of PubCaseFinder, including the new application programming interface and matching algorithm. Human Mutation, 43(6):734-742 (2022)
  2. Constructing Japanese MeSH term dictionaries related to the COVID-19 literature. Genomics & Informatics, 19(3): e25 (2021)
  3. A proof-of-concept study of extracting patient histories for rare/intractable diseases from social media. Genomics & Informatics, 18(2): e17 (2020)
  4. Split4Blank: Maintaining consistency while improving efficiency of loading RDF data with blank nodes. PLOS One, 14(6): e0217852 (2019)
  5. YummyData: Providing high-quality open life science data. Database, 2018:bay022 (2018)
  6. Semantic graph analysis for federated LOD surfing in life sciences. Lecture Notes in Computer Science, 10675: 268-276 (2017)
  7. The health care and life sciences community profile for dataset descriptions. PeerJ, 4(8):e2331 (2016)
  8. Efficiently finding paths between classes to build a SPARQL query for life-science databases. Lecture Notes in Computer Science, 9544: 321-330 (2016)
  9. Discriminative Application of String Similarity Methods to Chemical and Non-chemical Names for Biomedical Abbreviation Clustering. BMC Genomics, 13:s8 (2012)
  10. An approximation algorithm for the two-layered graph drawing problem. Lecture Notes in Computer Science, 1627: 81-91 (1999)
Patent
  1. 1. Document retrieval assisting method, system and service using closely displayed areas for titles and topics, Patent No: US 6457004 B1
  2. 2. Computer program embodied on a computer-readable medium for a document retrieval service that retrieves documents with a retrieval service agent computer, Patent No: US 6654738 B2
Award 1. Best In-Use Paper for 5th Joint International Semantic Technology Conference "Efficiently finding paths between classes to build a SPARQL query for life-science databases".
2. Best Paper Award for Information Processing Society of Japan (2000) "An approximation algorithm for the two-layered graph drawing problem."
3. Incentive Award for 7th Karuizawa Circuits and Systems Workshop "A parallel approximation algorithm for the minimum common supertree problem".
Grant-in-Aid for Scientific Research Support: Japan Society for Promotion of Science (JSPS) https://nrid.nii.ac.jp/en/nrid/1000010346108/
Affiliated academic society (Membership type) Information Processing Society of Japan, Japanese Society for Bioinformatics, The Japanese Society for Aartifical Intelligence
Education Field (Undergraduate level) Mathematics
Education Field (Graduate level) Information Science

Affiliation