Influence of Noise on the Inference of Dynamic Bayesian Networks from Short Time Series

Frank Emmert-Streib, Matthias Dehmer, Goekhan H. Bakir, Max Muehlhaeuser

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

Abstract

In this paper we investigate the influence of external noise on the inference of network structures. The purpose of our simulations is to gain insights in the experimental design of microarray experiments to infer, e.g., transcription regulatory networks from microarray experiments. Here external noise means, that the dynamics of the system under investigation, e.g., temporal changes of mRNA concentration, is affected by measurement errors. Additionally to external noise another problem occurs in the context of microarray experiments. Practically, it is not possible to monitor the mRNA concentration over an arbitrary long time period as demanded by the statistical methods used to learn the underlying network structure. For this reason, we use only short time series to make our simulations more biologically plausible.

Original languageEnglish
Title of host publicationProceedings Of World Academy Of Science, Engineering And Technology, Vol 10
EditorsC Ardil
PublisherWORLD ACAD SCI, ENG & TECH-WASET
Pages70-74
Number of pages5
ISBN (Print)*****************
Publication statusPublished - 2005
Externally publishedYes
Publication typeA4 Article in conference proceedings
EventConference of the World-Academy-of-Science-Engineering-and-Technology - Cracow, Poland
Duration: 16 Dec 200518 Dec 2005

Publication series

NameProceedings of World Academy of Science Engineering and Technology
PublisherWORLD ACAD SCI, ENG & TECH-WASET
Volume10
ISSN (Print)1307-6884

Conference

ConferenceConference of the World-Academy-of-Science-Engineering-and-Technology
Country/TerritoryPoland
Period16/12/0518/12/05

Keywords

  • Dynamic Bayesian networks
  • structure learning
  • gene networks
  • Markov chain Monte Carlo
  • microarray data
  • REGULATORY NETWORKS

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