@inproceedings{c402839db25a4fdeb8cafa20b700cf16,
title = "Influence of Noise on the Inference of Dynamic Bayesian Networks from Short Time Series",
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.",
keywords = "Dynamic Bayesian networks, structure learning, gene networks, Markov chain Monte Carlo, microarray data, REGULATORY NETWORKS",
author = "Frank Emmert-Streib and Matthias Dehmer and Bakir, {Goekhan H.} and Max Muehlhaeuser",
year = "2005",
language = "English",
isbn = "*****************",
series = "Proceedings of World Academy of Science Engineering and Technology",
publisher = "WORLD ACAD SCI, ENG & TECH-WASET",
pages = "70--74",
editor = "C Ardil",
booktitle = "Proceedings Of World Academy Of Science, Engineering And Technology, Vol 10",
note = "Conference of the World-Academy-of-Science-Engineering-and-Technology ; Conference date: 16-12-2005 Through 18-12-2005",
}