Mutagenicity Analysis Based on Rough Set Theory and Formal Concept Analysis

  • Mostafa A. Salama
  • Mohamed Mostafa M. Fouad
  • Nashwa El-Bendary
  • Aboul Ella Otifey Hassanien
Conference paper
Part of the Advances in Intelligent Systems and Computing book series (AISC, volume 235)


Most of the current Machine Learning applications in cheminformatics are black box applications. Support vector machine and neural networks are the most used classification techniques in prediction of the mutagenic activity of compounds. The problem of these techniques is that the rules/reasons of prediction are unknown. The rules could show the most important features/descrpitors of the compounds and the relations among them. This article proposes a model for generating the rules that governs prediction through the rough set theory. These rules, which based on two levels of selection for the highly discriminating power features, are visualized by lattice generated using the formal concept analysis approach. That is, better understanding of the reasons that leads to the mutagenic activity can be obtained. The resulted lattice shows that lipophilicity, number of nitrogen atoms, and electronegativity are the most important parameters in mutagenicity detection. Moreover, experimental results are compared against previous researches for validating the proposed model.


Support Vector Machine Formal Concept Target Class Formal Concept Analysis Feature Selection Technique 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  • Mostafa A. Salama
    • 1
  • Mohamed Mostafa M. Fouad
    • 2
  • Nashwa El-Bendary
    • 2
  • Aboul Ella Otifey Hassanien
    • 3
  1. 1.Scientific Research Group in Egypt (SRGE)British University in Egypt (BUE), Cairo - EgyptEl SheroukEgypt
  2. 2.Scientific Research Group in Egypt (SRGE)Arab Academy for Science, Technology, and Maritime Transport, Cairo - EgyptQism El-MontazaEgypt
  3. 3.Information Technology Dept., Faculty of Computers and Information, Scientific Research Group in Egypt (SRGE)Cairo UniversityCairoEgypt

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