Personalised Modelling on SNPs Data for Crohn’s Disease Prediction

  • Yingjie Hu
  • Nikola Kasabov
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7062)


This paper presents a study for investigating the feasibility of applying personalised modelling on single nucleotide polymorphisms (SNPs) data for disease analysis. We have applied our newly developed integrated method for personalised modelling (IMPM) on a real-world biomedical classification problem, which makes use of the SNPs data for crohn’s disease prediction. IMPM method allows for adaption and monitoring an individual’s model and outperforms global modelling methods for the SNPs data classification. Personalised modelling method produces a unique personalised profiling for an individual, which holds the promise of a new generation of analytical tools that can be used for personalised treatment.


Integrated method for personalised modelling IMPM SNPs evolutionary computation 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Yingjie Hu
    • 1
  • Nikola Kasabov
    • 1
  1. 1.The Knowledge Engineering and Discovery Research InstituteAuckland University of TechnologyNew Zealand

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