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Correcting for link loss in causal network inference caused by regulator interference
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Wang, Ying, Penfold, Christopher A., Hodgson, D. A., Gifford, Miriam L. and Burroughs, Nigel John (2014) Correcting for link loss in causal network inference caused by regulator interference. Bioinformatics, Volume 30 (Number 19). pp. 2779-2786. doi:10.1093/bioinformatics/btu388
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Official URL: http://dx.doi.org/10.1093/bioinformatics/btu388
Abstract
Motivation: There are a number of algorithms to infer causal regulatory networks from time-series (gene expression) data. Here we analyse the phenomena of regulator interference, where regulators with similar dynamics mutually suppress both the probability of regulating a target and the associated link strength; for instance interference between two identical strong regulators reduces link probabilities by about 50%.
Results: We construct a robust method to define an interference corrected causal network based on an analysis of the conditional link probabilities that recovers links lost through interference. On a large real network (Streptomyces coelicolor, phosphate depletion) we demonstrate that significant interference can occur between regulators with a correlation as low as 0.865, losing an estimated 34% of links by interference. However, levels of interference cannot be predicted from the correlation between regulators alone and are data specific. Validating against known networks we show that high numbers of functional links are lost by regulator interference. Performance against other methods on DREAM4 data is excellent.
Availability: The method is implemented in R and is publically available as the NIACS package at: http://www2.warwick.ac.uk/fac/sci/systemsbiology/research/software.
| Item Type: | Journal Article | ||||||||||
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| Subjects: | Q Science > QA Mathematics Q Science > QK Botany |
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| Divisions: | Faculty of Science, Engineering and Medicine > Science > Life Sciences (2010- ) Faculty of Science, Engineering and Medicine > Research Centres > Warwick Systems Biology Centre |
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| Library of Congress Subject Headings (LCSH): | Gene regulatory networks -- Mathematical models, Time-series analysis | ||||||||||
| Journal or Publication Title: | Bioinformatics | ||||||||||
| Publisher: | Oxford University Press | ||||||||||
| ISSN: | 1367-4803 | ||||||||||
| Official Date: | October 2014 | ||||||||||
| Dates: |
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| Volume: | Volume 30 | ||||||||||
| Number: | Number 19 | ||||||||||
| Page Range: | pp. 2779-2786 | ||||||||||
| DOI: | 10.1093/bioinformatics/btu388 | ||||||||||
| Status: | Peer Reviewed | ||||||||||
| Publication Status: | Published | ||||||||||
| Access rights to Published version: | Open Access | ||||||||||
| Funder: | Biotechnology and Biological Sciences Research Council (Great Britain) (BBSRC), Engineering and Physical Sciences Research Council (EPSRC) | ||||||||||
| Grant number: | BB/H109502/1 (BBSRC), EP/I036575/1 (EPSRC) |
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