title: Exact likelihood computation in Boolean networks with probabilistic time delays, and its application in signal network reconstruction.
abstract: BACKGROUND
  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.
  
  
  METHODS
  The algorithm is implemented in the statistical language R. Code and documentation are available at Bioinformatics online.
  
  
  BACKGROUND
  duemcke@mpipz.mpg.de or tresch@mpipz.mpg.de
  
  
  BACKGROUND
  Supplementary Materials are available at Bioinfomatics online.
authors.affiliation: Institute for Genetics, University of Cologne, 50674 Cologne, Max Planck Institute for Plant Breeding Research, 50829 Cologne, Gene Center, Department of Biochemistry, Ludwig-Maximilians University, 81379 Munich, Germany, Insitute for Functional Genomics, 93053 Regensburg, Germany, Department of Radiology, Center for Cancer Systems Biology, Stanford University, Stanford, CA 94305-5488, USA and ETH Zürich, Department of Biosystems Science and Engineering, Mattenstrasse 26 4058 Basel, Switzerland.
authors.forename: Sebastian
authors.initials: S
authors.lastname: Dümcke
authors.forename: Johannes
authors.initials: J
authors.lastname: Bräuer
authors.forename: Benedict
authors.initials: B
authors.lastname: Anchang
authors.forename: Rainer
authors.initials: R
authors.lastname: Spang
authors.forename: Niko
authors.initials: N
authors.lastname: Beerenwinkel
authors.forename: Achim
authors.initials: A
authors.lastname: Tresch
mesh_terms: D000465:Algorithms; D000818:Animals; D002454:Cell Differentiation; D053595:Embryonic Stem Cells / Q000166:cytology / Q000378:metabolism; D025461:Feedback, Physiological; D015870:Gene Expression; D051379:Mice; D011336:Probability; D034622:RNA Interference; D015398:Signal Transduction