Publications - Published papers
Please find below publications of our group. Currently, we list 565 papers. Some of the publications are in collaboration with the group of Sonja Prohaska and are also listed in the publication list for her individual group. Access to published papers (
) is restricted to our local network and chosen collaborators.
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) is restricted to our local network and chosen collaborators.
If you have problems accessing electronic information, please let us know:©NOTICE: All papers are copyrighted by the authors; If you would like to use all or a portion of any paper, please contact the author.
Prediction of lethal and synthetically lethal knock-outs in regulatory networks
Gunnar Boldhaus, Florian Greil, Konstantin Klemm
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Status: Published
Theory in Biosciences 132:17-25 (2013)
Abstract
The complex interactions involved in regulation of a cell's
function are captured by its interaction graph. More often
than not, detailed knowledge about enhancing or suppressive
regulatory influences and cooperative effects is lacking
and merely the presence or absence of directed interactions
is known. Here we investigate to which extent such reduced
information allows to forecast the effect of a knock-out or
a combination of knock-outs. Specifically we ask in how far
the lethality of eliminating nodes may be predicted by
their network centrality, such as degree and betweenness,
without knowing the function of the system. The function is
taken as the ability to reproduce a fixed point under a
discrete Boolean dynamics. We investigate two types of
stochastically generated networks: fully random networks
and structures grown with a mechanism of node duplication
and subsequent divergence of interactions. On all networks
we find that the out-degree is a good predictor of the
lethality of a single node knock-out. For knock-outs of
node pairs, the fraction of successors shared between the
two knocked-out nodes (out-overlap) is a good predictor of
synthetic lethality. Out-degree and out-overlap are locally
defined and computationally simple centrality measures that
provide a predictive power close to the optimal predictor.
Keywords
knock-out, synthetic lethality, prediction, network centrality, Boolean network