%0 Journal Article
	%A Frank Emmert Streib and  Matthias Dehmer and  Gökhan H. Bakır and  Max Mühlhauser
	%D 2007
	%J International Journal of Bioengineering and Life Sciences
	%B World Academy of Science, Engineering and Technology
	%I Open Science Index 10, 2007
	%T Influence of Noise on the Inference of Dynamic Bayesian Networks from Short Time Series
	%U https://publications.waset.org/pdf/6825
	%V 10
	%X 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.
	%P 575 - 579