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Dimension Concepts and Reduced Dimensions in Toxicological QShAR Databases as Tools for Data Quality Assessment

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Abstract

The dimensions of databases can be defined based on a variety of concepts, ranging from the standard tools of principal component analysis to context-biased approaches. The effective dimensions of databases, in particular the effective dimensions involving continua such as electron density data, provide a set of important tools for database comparisons and for the evaluation of some aspects of database quality. The problems associated with database comparisons and database mergers, such as those occurring in the process of database unification in the actual merger of two pharmaceutical companies, provide challenging tasks and opportunities for data science. Some of the tools for effective dimension reduction and dimension expansion are reviewed in the context of database quality control and conditions for database compatibility are presented. A common misconception affecting data sampling techniques for data quality evaluation is discussed and methods for circumventing the associated sampling errors are described.

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Authors and Affiliations

  1. Mathematical Chemistry Research Unit, Department of Chemistry and Department of Mathematics and Statistics, University of Saskatchewan, 110 Science Place, Saskatoon, SK, Canada, S7N 5C9

    Peter Warburton

  2. Institute for Advanced Study, Collegium Budapest, Szentháromság u. 2, 1014, Budapest, Hungary

    Paul G. Mezey & E. Jako

  3. Committee for Data in Science and Technology, CODATA Secretariat, CODATA (ICSU/UNESCO), 51 Bd de Montmorency, 75016, Paris, France

    Paul G. Mezey

  4. Institute of Chemistry, University of Budapest, Pázmány Péter Sétány 2, Budapest, Hungary

    Zsolt Szekeres

Authors
  1. Paul G. Mezey
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  2. Peter Warburton
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  3. E. Jako
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  4. Zsolt Szekeres
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Correspondence to Paul G. Mezey.

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Mezey, P.G., Warburton, P., Jako, E. et al. Dimension Concepts and Reduced Dimensions in Toxicological QShAR Databases as Tools for Data Quality Assessment. Journal of Mathematical Chemistry 30, 375–387 (2001). https://doi.org/10.1023/A:1015138426162

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