Inferring biomolecular regulatory networks from phase portraits of time-series expression profiles

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Reverse engineering of biomolecular regulatory networks such as gene regulatory networks, protein interaction networks, and metabolic networks has received an increasing attention as more high-throughput time-series measurements become available. In spite of various approaches developed from this motivation, it still remains as a challenging subject to develop a new reverse engineering scheme that can effectively uncover the functional interaction structure of a biomolecular network from given time-series expression profiles (TSEPs). We propose a new reverse engineering scheme that makes use of phase portraits constructed by projection of every two TSEPs into respective phase planes. We introduce two measures of a slope index (SI) and a winding index (WI) to quantify the interaction properties embedded in the phase portrait. Based on the SI and WI, we can reconstruct the functional interaction network in a very efficient and systematic way with better inference results compared to previous approaches. By using the SI, we can also estimate the time-lag accompanied with the interaction between molecular components of a network. (c) 2006 Federation of European Biochemical Societies. Published by Elsevier B.V. All rights reserved.
Publisher
ELSEVIER SCIENCE BV
Issue Date
2006-06
Language
English
Article Type
Article
Keywords

GENE-EXPRESSION; INFERENCE; PROTEIN; CELLS

Citation

FEBS LETTERS, v.580, pp.3511 - 3518

ISSN
0014-5793
DOI
10.1016/j.febslet.2006.05.035
URI
http://hdl.handle.net/10203/91869
Appears in Collection
BiS-Journal Papers(저널논문)
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