Universität zu Köln

Duemcke, Sebastian, Braeuer, Johannes, Anchang, Benedict, Spang, Rainer ORCID: 0000-0002-1326-4297, Beerenwinkel, Niko and Tresch, Achim (2014). Exact likelihood computation in Boolean networks with probabilistic time delays, and its application in signal network reconstruction. Bioinformatics, 30 (3). S. 414 - 420. OXFORD: OXFORD UNIV PRESS. ISSN 1460-2059

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Abstract

Motivation: For biological pathways, it is common to measure a gene expression time series after various knockdowns of genes that are putatively involved in the process of interest. These interventional time-resolved data are most suitable for the elucidation of dynamic causal relationships in signaling networks. Even with this kind of data it is still a major and largely unsolved challenge to infer the topology and interaction logic of the underlying regulatory network. Results: In this work, we present a novel model-based approach involving Boolean networks to reconstruct small to medium-sized regulatory networks. In particular, we solve the problem of exact likelihood computation in Boolean networks with probabilistic exponential time delays. Simulations demonstrate the high accuracy of our approach. We apply our method to data of Ivanova et al. (2006), where RNA interference knockdown experiments were used to build a network of the key regulatory genes governing mouse stem cell maintenance and differentiation. In contrast to previous analyses of that data set, our method can identify feedback loops and provides new insights into the interplay of some master regulators in embryonic stem cell development.

Item Type:	Journal Article
Creators:	Creators Email ORCID ORCID Put Code Duemcke, Sebastian UNSPECIFIED UNSPECIFIED UNSPECIFIED Braeuer, Johannes UNSPECIFIED UNSPECIFIED UNSPECIFIED Anchang, Benedict UNSPECIFIED UNSPECIFIED UNSPECIFIED Spang, Rainer UNSPECIFIED orcid.org/0000-0002-1326-4297 UNSPECIFIED Beerenwinkel, Niko UNSPECIFIED UNSPECIFIED UNSPECIFIED Tresch, Achim UNSPECIFIED UNSPECIFIED UNSPECIFIED
URN:	urn:nbn:de:hbz:38-446995
DOI:	10.1093/bioinformatics/btt696
Journal or Publication Title:	Bioinformatics
Volume:	30
Number:	3
Page Range:	S. 414 - 420
Date:	2014
Publisher:	OXFORD UNIV PRESS
Place of Publication:	OXFORD
ISSN:	1460-2059
Language:	English
Faculty:	Unspecified
Divisions:	Unspecified
Subjects:	no entry
Uncontrolled Keywords:	Keywords Language NESTED EFFECTS MODELS; BAYESIAN NETWORKS; REGULATORY NETWORKS; STEM-CELLS; EXPRESSION Multiple languages Biochemical Research Methods; Biotechnology & Applied Microbiology; Computer Science, Interdisciplinary Applications; Mathematical & Computational Biology; Statistics & Probability Multiple languages
URI:	http://kups.ub.uni-koeln.de/id/eprint/44699