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2002 Fiscal Year Final Research Report Summary

DEVELOPMENT OF A GRAPH STRUCTURE DATAMINING METHOD AND IDENTIFICATION SYSTEM OF ACTIVE MOLECULE SUBSTRU CTURES

Research Project

Project/Area Number 12480088
Research Category

Grant-in-Aid for Scientific Research (B)

Allocation TypeSingle-year Grants
Section一般
Research Field Intelligent informatics
Research InstitutionOSAKA UNIVERSITY

Principal Investigator

WASHIO Takashi  THE INSTITUTE OF ASSOCIATE SCIENTIFIC AND PROFESSOR INDUSTRIAL RESEARCH, 産業科学研究所, 助教授 (00192815)

Co-Investigator(Kenkyū-buntansha) YOSHIDA Tetsuya  THE INSTITUTE OF RESEACH SCIENTIFIC AND ASSO CIATE INDUSTRIAL RESEARCH, 産業科学研究所, 助手 (80294164)
OKADA Takashi  EDUCATIONCENTER PROFESSOR OF INFORMATION AND MEDIA, KUWANSEI GAKUIN DAIGAKU, 情報メディア教育センター, 教授 (00103135)
MOTODA Hiroshi  THE INSTITUTE OF PROFESSOR SCIENTIFIC AND INDUSTRIAL RESEARCH, 産業科学研究所, 教授 (00283804)
Project Period (FY) 2000 – 2002
KeywordsGRAPH STRUCTURE / DATA MINING / ADJACENCY MATRIX / CANONICAL FORM / ISOMOPHISM / MOLECULAR STRUCTURE / CARCINOGENESITY / MUNAGENESITY
Research Abstract

In the first fiscal year, the theoretical framework of graph structure data mining was investigated, and a prototype system for active molecule substructure identification was developed. In this work, the representation of graph structure data in computers and search principle of characteristic graph patterns are studied. Them, the survey of techniques in chemistry which can be introduced to our work has been conducted, and these techniques were reflected in the prototype system. Finally, the basic performance of the prototype system has been evaluated through the substructure extraction in carcinogenetic and mutagenetic chemical component data.
In the nest fiscal year, the framework of the graph structure data mining was extended to be more efficient in terms of computation time and memory consumption, and the real scale system for active molecule substructure identification has been developed. The algorithm for the efficient computation time and memory consumption was developed, and under the comparison with the conventional techniques in chemistry, the function of the real system was designed. Then, the principle and the algorithm of the real system was modified and extended to enable the graph structure data mining on the massive graph structure data.
In the final fiscal year, further functions desired to be implemented in the view of chemical analysis were investigated based on the real system developed in the former year, and some functions which can be implemented feasibly were added to the real system. Then, from the view points of the chemical engineering and the computational theory, the practicality and the wide applicability of the real system have been evaluated. Through these evaluations, the practical and high performance of the developed real sysem has been confirmed. The effort to develop commercial system under collaboration with industries is currently underway.

  • Research Products

    (12 results)

All Other

All Publications (12 results)

  • [Publications] A.Inokuchi, T.Washio, T.Okada, H.Motoda: "Applying the Apriori-based Graph Mining Method to Mutagenesis Data Analysis"Journal of Computer Aided Chemistry. Vol.2. 87-92 (2001)

    • Description
      「研究成果報告書概要(和文)」より
  • [Publications] Takashi Matsuda, Hiroshi Motoda, Tetsuya Yoshida, Takashi Washio: "Preliminary Analysis of Hepatitis Data by Beam-wise Graph-Based Induction"Working Notes of Discovery Challenge Workshop Notes, Helsinki, Finland, ECML/PKDD-2002 Workshop Proceedings, Petr Berka, Eds.. ECML/PKDD. 60-72 (2002)

    • Description
      「研究成果報告書概要(和文)」より
  • [Publications] 西村芳男, 鷲尾隆, 吉田哲也, 元田浩, 猪口明博: "AGMの性能評価と変異原性化学物質分子構造実データヘの適用"第3回データマイニングワークショップ(日本ソフトウエア科学会). 11-20 (2002)

    • Description
      「研究成果報告書概要(和文)」より
  • [Publications] 西村芳男, 鷲尾 隆, 吉田哲也, 元田 浩, 猪口明博, 岡田 孝: "AGMによる立体構造と生理活性の相関解析"第30回構造活性相関シンポジウム,K16(日本化学学会). 53-56 (2002)

    • Description
      「研究成果報告書概要(和文)」より
  • [Publications] T Akihiro Inikuchi, Takashi Washio, Yoshio Nishimura, Hiroshi Motoda: "General Freamework for Mining Frequent Patterns in Structur"Proceedings of International Workshop on Active Mining. ICDM. 23-30 (2002)

    • Description
      「研究成果報告書概要(和文)」より
  • [Publications] Akihiro Inokuchi, Takashi Wasiho, Hiroshi Motoda: "Complete Mining of Frequent Patterns from Graphs : Mining Graph Data"Machine Learning. Vol.50. 321-354 (2003)

    • Description
      「研究成果報告書概要(和文)」より
  • [Publications] A.Inokuchi, T.Washio, T.Okada and H.Motoda: "Applying the Apriori-based Graph Mining Method to Mutagenesis Data Analysis"Journal of Computer Aided Chemistry. Vol.2. 87-92 (2001)

    • Description
      「研究成果報告書概要(欧文)」より
  • [Publications] Takashi Matsuda, Hiroshi Motoda, Tetsuya Yoshida and Takashi Washio: "Preliminary Analysis of Hepatitis Data by Beam-wise Graph-Based Induction"Working Notes of Discovery Challenge Workshop Notes, Helsinki, Finland, ECML/PKDD-2002 Workshop Proceedings, Petr Berka, Eds., ECML/PKDD. 60-72 (2002)

    • Description
      「研究成果報告書概要(欧文)」より
  • [Publications] Yoshio Nishimura, Takashi Washio, Tetsuya Yoshida, Hiroshi Motoda and Akihiro Inokuchi: "Performance Evaluation ofAGM and Its Application to Mutagenesis Chemical Compound Data"The 3^<rd> Data Mining Workshop, Japan Society for Software Science and Technology. 11-20 (2002)

    • Description
      「研究成果報告書概要(欧文)」より
  • [Publications] Yoshio Nishimura, Takashi Washio, Tetsuya Yoshida, Hiroshi Motoda, Akihiro Inokuchi and Takashi Okada: "Structural Correlation Analysis with Bio-Chemical Activity by AGM"The 30^<th> Structural Correlation Analysis Symposium, The Chemical Society of Japan. 53-56 (2002)

    • Description
      「研究成果報告書概要(欧文)」より
  • [Publications] Akihiro Inikuchi, Takashi Washio, Yoshio Nishimura and Hiroshi Motoda: "General Freamework for Mining Frequent Patterns in Structure"Proceedings of International Workshop on Active Mining, ICDM. 23-30 (2002)

    • Description
      「研究成果報告書概要(欧文)」より
  • [Publications] Akihiro Inokuchi, Takashi Wasiho and Hiroshi Motoda: "Complete Mining of Freqent Patterns from Graphs: Mining Graph Data"Machine Learning. Vol.50. 321-354 (2003)

    • Description
      「研究成果報告書概要(欧文)」より

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Published: 2004-04-14  

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