Staff Publications

Staff Publications

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    'Staff publications' is the digital repository of Wageningen University & Research

    'Staff publications' contains references to publications authored by Wageningen University staff from 1976 onward.

    Publications authored by the staff of the Research Institutes are available from 1995 onwards.

    Full text documents are added when available. The database is updated daily and currently holds about 240,000 items, of which 72,000 in open access.

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Record number 420173
Title Mutational Robustness of Gene Regulatory Networks
Author(s) Dijk, A.D.J. van; Mourik, S. van; Ham, R.C.H.J. van
Source PLoS One 7 (2012)1. - ISSN 1932-6203 - 9 p.
DOI https://doi.org/10.1371/journal.pone.0030591
Department(s) Biometris (WU MAT)
PRI BIOS Applied Bioinformatics
PE&RC
Publication type Refereed Article in a scientific journal
Publication year 2012
Keyword(s) transcription factor-binding - chip-seq - expression - evolution - evolvability - noise - yeast - autoregulation - dimerization - mechanisms
Abstract Mutational robustness of gene regulatory networks refers to their ability to generate constant biological output upon mutations that change network structure. Such networks contain regulatory interactions (transcription factor – target gene interactions) but often also protein-protein interactions between transcription factors. Using computational modeling, we study factors that influence robustness and we infer several network properties governing it. These include the type of mutation, i.e. whether a regulatory interaction or a protein-protein interaction is mutated, and in the case of mutation of a regulatory interaction, the sign of the interaction (activating vs. repressive). In addition, we analyze the effect of combinations of mutations and we compare networks containing monomeric with those containing dimeric transcription factors. Our results are consistent with available data on biological networks, for example based on evolutionary conservation of network features. As a novel and remarkable property, we predict that networks are more robust against mutations in monomer than in dimer transcription factors, a prediction for which analysis of conservation of DNA binding residues in monomeric vs. dimeric transcription factors provides indirect evidence
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