Skip navigation
SuUB logo
DSpace logo

  • Home
  • Institutions
    • University of Bremen
    • City University of Applied Sciences
    • Bremerhaven University of Applied Sciences
  • Sign on to:
    • My Media
    • Receive email
      updates
    • Edit Account details

Citation link: https://nbn-resolving.de/urn:nbn:de:gbv:46-00102768-10
00102768-1.pdf
OpenAccess
 
copyright

Künstliche neuronale Netze in der genetischen Epidemiologie


File Description SizeFormat
00102768-1.pdf11.21 MBAdobe PDFView/Open
Other Titles: Artificial neural networks in genetic epidemiology
Authors: Günther, Frauke 
Supervisor: Pigeot, Iris  
1. Expert: Pigeot, Iris  
Experts: Brannath, Werner  
Abstract: 
Gene-gene and gene-environment interactions play an important role in the etiological pathway of many complex diseases. However, common statistical methods like regression models have problems to capture the complex interplay between genetic and non-genetic factors. Artificial neural networks provide a great flexibility to model functional relationships and thus are a promising statistical tool to handle the complexity of biological interactions. The aim of this thesis is to explore the ability of neural networks to capture different structures of gene-gene and gene-environment interactions and to identify gene-gene interactions in simulation studies. In addition, the consistency of the estimated weights is investigated for non-identified neural networks. In summary, neural networks prove successful for exploratory analyses and particularly can be used if limited information on the kind of functional relationship between influencing factors and the investigated outcome is available.
Keywords: Artificial neural networks; gene-gene interaction; gene-environment interaction; genetic epidemiology; epistasis; statistics
Issue Date: 15-Aug-2012
Type: Dissertation
Secondary publication: no
URN: urn:nbn:de:gbv:46-00102768-10
Institution: Universität Bremen 
Faculty: Fachbereich 03: Mathematik/Informatik (FB 03) 
Appears in Collections:Dissertationen

  

Page view(s)

368
checked on May 9, 2025

Download(s)

125
checked on May 9, 2025

Google ScholarTM

Check


Items in Media are protected by copyright, with all rights reserved, unless otherwise indicated.

Legal notice -Feedback -Data privacy
Media - Extension maintained and optimized by Logo 4SCIENCE