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Riskoweb: Web-Based Genetic Profiling to Complex Disease Using Genome-Wide SNP Markers

  • Sergio Torres-Sánchez
  • Rosana Montes-Soldado
  • Nuria Medina-Medina
  • Andrés R. Masegosa
  • María Mar Abad-Grau
Part of the Advances in Intelligent and Soft Computing book series (AINSC, volume 93)

Abstract

Assessing risk susceptibility of individuals to a complex disease is becoming an interesting prevention tool specially recommended for those with ancestors or other relatives affected by the disease. As genome-wide DNA sequencing is getting more affordable, more dense genotyping is performed and accuracy is increased. Therefore, health public services may consider the results of this approach in their preventing plans and physicians be encouraged to perform these risk tests. A web-based tool has been built for risk assessing of complex diseases and its knowledge base is currently filled with multiple sclerosis risk variants and their effect on the disease. The genetic profiling is calculated by using a Naive Bayes network, which it has been shown to provide highly accurate results as long as dense genotyping, haplotype reconstruction and several markers at a time are considered.

Keywords

Multiple Sclerosis Random Forest Complex Disease Risk Locus Genetic Risk Score 
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-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Sergio Torres-Sánchez
    • 1
  • Rosana Montes-Soldado
    • 1
  • Nuria Medina-Medina
    • 1
  • Andrés R. Masegosa
    • 2
  • María Mar Abad-Grau
    • 1
  1. 1.Department of Computer Languages and Systems - CITICUniversity of GranadaSpain
  2. 2.Department of Computer Science and Artificial Intelligence - CITICUniversity of GranadaSpain

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