Background: For large-scale biological networks represented as signed graphs, the index of frustration measures how far a network is from a monotone system, i.e., how incoherently the system responds to perturbations.Results: In this paper we find that the frustration is systematically lower in transcriptional networks (modeled at functional level) than in signaling and metabolic networks (modeled at stoichiometric level). A possible interpretation of this result is in terms of energetic cost of an interaction: an erroneous or contradictory transcriptional action costs much more than a signaling/metabolic error, and therefore must be avoided as much as possible. Averaging over all possible perturbations, however, we also find that unlike fo...
We examine the capacity of artificial biomolecular networks to respond to perturbations with structu...
A framework for studying the behavior of a classically frustrated signed network in the process of r...
<div><p>Cells live in changing, dynamic environments. To understand cellular decision-making, we mus...
for Monotonicity, frustration, and ordered response: an analysis of the energy landscape of perturbe...
Metabolic networks have gained broad attention in recent years as a result of their important roles ...
<p>Complex networks have been successfully employed to represent different levels of biological syst...
BackgroundMany studies of biochemical networks have analyzed network topology. Such work has suggest...
Biological networks exhibit intriguing topological properties such as small-worldness. In this paper...
For almost 10 years, topological analysis of different large-scale biological networks (metabolic re...
<div><p>The topology of cellular circuits (the who-interacts-with-whom) is key to understand their r...
International audienceBackground: Metabolic networks reflect the relationships between metabolites (...
Abstract The deficiency of a (bio)chemical reaction network can be conceptually interpreted as a mea...
We started offering an introduction to very basic aspects of molecular biology, for the reader comin...
Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Physics, 2004.Includes bibliographi...
LaTeX, 30 pages, 20 picturesWe consider a model of large regulatory gene expression networks where t...
We examine the capacity of artificial biomolecular networks to respond to perturbations with structu...
A framework for studying the behavior of a classically frustrated signed network in the process of r...
<div><p>Cells live in changing, dynamic environments. To understand cellular decision-making, we mus...
for Monotonicity, frustration, and ordered response: an analysis of the energy landscape of perturbe...
Metabolic networks have gained broad attention in recent years as a result of their important roles ...
<p>Complex networks have been successfully employed to represent different levels of biological syst...
BackgroundMany studies of biochemical networks have analyzed network topology. Such work has suggest...
Biological networks exhibit intriguing topological properties such as small-worldness. In this paper...
For almost 10 years, topological analysis of different large-scale biological networks (metabolic re...
<div><p>The topology of cellular circuits (the who-interacts-with-whom) is key to understand their r...
International audienceBackground: Metabolic networks reflect the relationships between metabolites (...
Abstract The deficiency of a (bio)chemical reaction network can be conceptually interpreted as a mea...
We started offering an introduction to very basic aspects of molecular biology, for the reader comin...
Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Physics, 2004.Includes bibliographi...
LaTeX, 30 pages, 20 picturesWe consider a model of large regulatory gene expression networks where t...
We examine the capacity of artificial biomolecular networks to respond to perturbations with structu...
A framework for studying the behavior of a classically frustrated signed network in the process of r...
<div><p>Cells live in changing, dynamic environments. To understand cellular decision-making, we mus...