Towards an intelligent data type for toxicity

Damian McCourt, Jesús López, Emilio Benfenati, Paolo Mazzatorta, Mathilde Romberg, Bernd Schuller, Werner Dubitzky

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Data analysis in bioinformatics relies heavily on statistics and machine learning. Many of these approaches use simplistic formats for representing real-world objects. Recent computational methods rely on more structured representations. This paper presents an object-oriented approach to model toxicity as an intelligent data type. The intelligent data type representing toxicity is potentially useful for a wide range of bioinformatics methodologies and systems including data warehousing, data mining, knowledge-based and simulation systems, and within distributed computing environments such as emerging Grid applications.

Original languageEnglish
Title of host publicationProceedings of the International Conference on Artificial Intelligence IC-AI 2003
EditorsH.R. Arabnia, R. Joshua, Y. Mun, H.R. Arabnia, R. Joshua, Y. Mun
Pages328-334
Number of pages7
Volume1
Publication statusPublished - 2003
EventProceedings of the International Conference on Artificial Intelligence, IC-AI 2003 - Las Vegas, NV, United States
Duration: Jun 23 2003Jun 26 2003

Other

OtherProceedings of the International Conference on Artificial Intelligence, IC-AI 2003
CountryUnited States
CityLas Vegas, NV
Period6/23/036/26/03

Keywords

  • Bioinformatics
  • Data integration
  • Data mining
  • Grid
  • Intelligent data types
  • Toxicity

ASJC Scopus subject areas

  • Artificial Intelligence

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