Andreas Wagner

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The metabolic network of the catabolic, energy and biosynthetic metabolism of Escherichia coli is a paradigmatic case for the large genetic and metabolic networks that functional genomics efforts are beginning to elucidate. To analyse the structure of previously unknown networks involving hundreds or thousands of components by simple visual inspection is(More)
Understanding the relationship between robustness and evolvability is key to understand how living things can withstand mutations, while producing ample variation that leads to evolutionary innovations. Mutational robustness and evolvability, a system's ability to produce heritable variation, harbour a paradoxical tension. On one hand, high robustness(More)
In this paper, the structure and evolution of the protein interaction network of the yeast Saccharomyces cerevisiae is analyzed. The network is viewed as a graph whose nodes correspond to proteins. Two proteins are connected by an edge if they interact. The network resembles a random graph in that it consists of many small subnets (groups of proteins that(More)
The history of life involves countless evolutionary innovations, a steady stream of ingenuity that has been flowing for more than 3 billion years. Very little is known about the principles of biological organization that allow such innovation. Here, we examine these principles for evolutionary innovation in gene expression patterns. To this end, we study a(More)
The topology of cellular circuits (the who-interacts-with-whom) is key to understand their robustness to both mutations and noise. The reason is that many biochemical parameters driving circuit behavior vary extensively and are thus not fine-tuned. Existing work in this area asks to what extent the function of any one given circuit is robust. But is high(More)
During the development of a multicellular organism from a zygote, a large number of epigenetic interactions take place on every level of suborganismal organization. This raises the possibility that the system of epigenetic interactions may compensate or "buffer" some of the changes that occur as mutations on its lowest levels, and thus stabilize the(More)
Robustness is the invariance of phenotypes in the face of perturbation. The robustness of phenotypes appears at various levels of biological organization, including gene expression, protein folding, metabolic flux, physiological homeostasis, development, and even organismal fitness. The mechanisms underlying robustness are diverse, ranging from(More)
Genome sequencing is now advancing at a frenetic pace, which has the consequence that many organisms now being sequenced have not had their biochemistry extensively studied. Thus, the metabolic phenotype of these organisms has to be determined using annotated genome sequence data. Ideally, this determination should be automated, but that would require clear(More)
I here estimate the energy cost of changes in gene expression for several thousand genes in the yeast Saccharomyces cerevisiae. A doubling of gene expression, as it occurs in a gene duplication event, is significantly selected against for all genes for which expression data is available. It carries a median selective disadvantage of s > 10(-5), several(More)
A biological system is robust to mutations if it continues to function after genetic changes in its parts. Such robustness is pervasive on different levels of biological organization, from macromolecules to genetic networks and whole organisms. I here ask which of two possible causes of such robustness are more important on a genome-wide scale, for systems(More)