author_facet Manke, Thomas
Demetrius, Lloyd
Vingron, Martin
Manke, Thomas
Demetrius, Lloyd
Vingron, Martin
author Manke, Thomas
Demetrius, Lloyd
Vingron, Martin
spellingShingle Manke, Thomas
Demetrius, Lloyd
Vingron, Martin
Journal of The Royal Society Interface
An entropic characterization of protein interaction networks and cellular robustness
Biomedical Engineering
Biochemistry
Biomaterials
Bioengineering
Biophysics
Biotechnology
author_sort manke, thomas
spelling Manke, Thomas Demetrius, Lloyd Vingron, Martin 1742-5689 1742-5662 The Royal Society Biomedical Engineering Biochemistry Biomaterials Bioengineering Biophysics Biotechnology http://dx.doi.org/10.1098/rsif.2006.0140 <jats:p> The structure of molecular networks is believed to determine important aspects of their cellular function, such as the organismal resilience against random perturbations. Ultimately, however, cellular behaviour is determined by the dynamical processes, which are constrained by network topology. The present work is based on a fundamental relation from dynamical systems theory, which states that the macroscopic resilience of a steady state is correlated with the uncertainty in the underlying microscopic processes, a property that can be measured by entropy. Here, we use recent network data from large-scale protein interaction screens to characterize the diversity of possible pathways in terms of network entropy. This measure has its origin in statistical mechanics and amounts to a global characterization of both structural and dynamical resilience in terms of microscopic elements. We demonstrate how this approach can be used to rank network elements according to their contribution to network entropy and also investigate how this suggested ranking reflects on the functional data provided by gene knockouts and RNAi experiments in yeast and <jats:italic>Caenorhabditis elegans</jats:italic> . Our analysis shows that knockouts of proteins with large contribution to network entropy are preferentially lethal. This observation is robust with respect to several possible errors and biases in the experimental data. It underscores the significance of entropy as a fundamental invariant of the dynamical system, and as a measure of structural and dynamical properties of networks. Our analytical approach goes beyond the phenomenological studies of cellular robustness based on local network observables, such as connectivity. One of its principal achievements is to provide a rationale to study proxies of cellular resilience and rank proteins according to their importance within the global network context. </jats:p> An entropic characterization of protein interaction networks and cellular robustness Journal of The Royal Society Interface
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title An entropic characterization of protein interaction networks and cellular robustness
title_unstemmed An entropic characterization of protein interaction networks and cellular robustness
title_full An entropic characterization of protein interaction networks and cellular robustness
title_fullStr An entropic characterization of protein interaction networks and cellular robustness
title_full_unstemmed An entropic characterization of protein interaction networks and cellular robustness
title_short An entropic characterization of protein interaction networks and cellular robustness
title_sort an entropic characterization of protein interaction networks and cellular robustness
topic Biomedical Engineering
Biochemistry
Biomaterials
Bioengineering
Biophysics
Biotechnology
url http://dx.doi.org/10.1098/rsif.2006.0140
publishDate 2006
physical 843-850
description <jats:p> The structure of molecular networks is believed to determine important aspects of their cellular function, such as the organismal resilience against random perturbations. Ultimately, however, cellular behaviour is determined by the dynamical processes, which are constrained by network topology. The present work is based on a fundamental relation from dynamical systems theory, which states that the macroscopic resilience of a steady state is correlated with the uncertainty in the underlying microscopic processes, a property that can be measured by entropy. Here, we use recent network data from large-scale protein interaction screens to characterize the diversity of possible pathways in terms of network entropy. This measure has its origin in statistical mechanics and amounts to a global characterization of both structural and dynamical resilience in terms of microscopic elements. We demonstrate how this approach can be used to rank network elements according to their contribution to network entropy and also investigate how this suggested ranking reflects on the functional data provided by gene knockouts and RNAi experiments in yeast and <jats:italic>Caenorhabditis elegans</jats:italic> . Our analysis shows that knockouts of proteins with large contribution to network entropy are preferentially lethal. This observation is robust with respect to several possible errors and biases in the experimental data. It underscores the significance of entropy as a fundamental invariant of the dynamical system, and as a measure of structural and dynamical properties of networks. Our analytical approach goes beyond the phenomenological studies of cellular robustness based on local network observables, such as connectivity. One of its principal achievements is to provide a rationale to study proxies of cellular resilience and rank proteins according to their importance within the global network context. </jats:p>
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author Manke, Thomas, Demetrius, Lloyd, Vingron, Martin
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author_sort manke, thomas
container_issue 11
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container_title Journal of The Royal Society Interface
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description <jats:p> The structure of molecular networks is believed to determine important aspects of their cellular function, such as the organismal resilience against random perturbations. Ultimately, however, cellular behaviour is determined by the dynamical processes, which are constrained by network topology. The present work is based on a fundamental relation from dynamical systems theory, which states that the macroscopic resilience of a steady state is correlated with the uncertainty in the underlying microscopic processes, a property that can be measured by entropy. Here, we use recent network data from large-scale protein interaction screens to characterize the diversity of possible pathways in terms of network entropy. This measure has its origin in statistical mechanics and amounts to a global characterization of both structural and dynamical resilience in terms of microscopic elements. We demonstrate how this approach can be used to rank network elements according to their contribution to network entropy and also investigate how this suggested ranking reflects on the functional data provided by gene knockouts and RNAi experiments in yeast and <jats:italic>Caenorhabditis elegans</jats:italic> . Our analysis shows that knockouts of proteins with large contribution to network entropy are preferentially lethal. This observation is robust with respect to several possible errors and biases in the experimental data. It underscores the significance of entropy as a fundamental invariant of the dynamical system, and as a measure of structural and dynamical properties of networks. Our analytical approach goes beyond the phenomenological studies of cellular robustness based on local network observables, such as connectivity. One of its principal achievements is to provide a rationale to study proxies of cellular resilience and rank proteins according to their importance within the global network context. </jats:p>
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spelling Manke, Thomas Demetrius, Lloyd Vingron, Martin 1742-5689 1742-5662 The Royal Society Biomedical Engineering Biochemistry Biomaterials Bioengineering Biophysics Biotechnology http://dx.doi.org/10.1098/rsif.2006.0140 <jats:p> The structure of molecular networks is believed to determine important aspects of their cellular function, such as the organismal resilience against random perturbations. Ultimately, however, cellular behaviour is determined by the dynamical processes, which are constrained by network topology. The present work is based on a fundamental relation from dynamical systems theory, which states that the macroscopic resilience of a steady state is correlated with the uncertainty in the underlying microscopic processes, a property that can be measured by entropy. Here, we use recent network data from large-scale protein interaction screens to characterize the diversity of possible pathways in terms of network entropy. This measure has its origin in statistical mechanics and amounts to a global characterization of both structural and dynamical resilience in terms of microscopic elements. We demonstrate how this approach can be used to rank network elements according to their contribution to network entropy and also investigate how this suggested ranking reflects on the functional data provided by gene knockouts and RNAi experiments in yeast and <jats:italic>Caenorhabditis elegans</jats:italic> . Our analysis shows that knockouts of proteins with large contribution to network entropy are preferentially lethal. This observation is robust with respect to several possible errors and biases in the experimental data. It underscores the significance of entropy as a fundamental invariant of the dynamical system, and as a measure of structural and dynamical properties of networks. Our analytical approach goes beyond the phenomenological studies of cellular robustness based on local network observables, such as connectivity. One of its principal achievements is to provide a rationale to study proxies of cellular resilience and rank proteins according to their importance within the global network context. </jats:p> An entropic characterization of protein interaction networks and cellular robustness Journal of The Royal Society Interface
spellingShingle Manke, Thomas, Demetrius, Lloyd, Vingron, Martin, Journal of The Royal Society Interface, An entropic characterization of protein interaction networks and cellular robustness, Biomedical Engineering, Biochemistry, Biomaterials, Bioengineering, Biophysics, Biotechnology
title An entropic characterization of protein interaction networks and cellular robustness
title_full An entropic characterization of protein interaction networks and cellular robustness
title_fullStr An entropic characterization of protein interaction networks and cellular robustness
title_full_unstemmed An entropic characterization of protein interaction networks and cellular robustness
title_short An entropic characterization of protein interaction networks and cellular robustness
title_sort an entropic characterization of protein interaction networks and cellular robustness
title_unstemmed An entropic characterization of protein interaction networks and cellular robustness
topic Biomedical Engineering, Biochemistry, Biomaterials, Bioengineering, Biophysics, Biotechnology
url http://dx.doi.org/10.1098/rsif.2006.0140