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Spiral Mining Using Attributes from 3D Molecular Structures

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Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 3430))

Abstract

Active responses from analysts play an essential role in obtaining insights into structure activity relationships (SAR) from drug data. Experts often think of hypotheses, and they want to reflect these ideas in the attribute generation and selection process. We analyzed the SAR of dopamine agonists and antagonists using the cascade model. The presence or absence of linear fragments in molecules constitutes the core attribute in the mining. In this paper, we generated attributes indicating the presence of hydrogen bonds from 3D coordinates of molecules. Various improvements in the fragment expressions are also introduced following the suggestions of chemists. Attribute selection from the generated fragments is another key step in mining. Close interactions between chemists and system developers have enabled spiral mining, in which the analysis results are incorporated into the development of new functions in the mining system. All these factors are necessary for success in SAR mining.

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© 2005 Springer-Verlag Berlin Heidelberg

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Okada, T., Yamakawa, M., Niitsuma, H. (2005). Spiral Mining Using Attributes from 3D Molecular Structures. In: Tsumoto, S., Yamaguchi, T., Numao, M., Motoda, H. (eds) Active Mining. Lecture Notes in Computer Science(), vol 3430. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11423270_16

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  • DOI: https://doi.org/10.1007/11423270_16

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-26157-5

  • Online ISBN: 978-3-540-31933-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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