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  • A Wagner
  • 2001
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 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)
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)
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)
Large scale gene perturbation experiments generate information about the number of genes whose activity is directly or indirectly affected by a gene perturbation. From this information, one can numerically estimate coarse structural network features such as the total number of direct regulatory interactions and the number of isolated subnetworks in a(More)
I present an algorithm to reconstruct direct regulatory interactions in gene networks from the effects of genetic perturbations on gene activity. Genomic technology has made feasible large-scale experiments that perturb the activity of many genes and then assess the effect of each individual perturbation on all other genes in an organism. Current(More)
  • A Wagner
  • 2000
The neutralist perspective on molecular evolution maintains that the vast majority of mutations affecting gene function are neutral or deleterious. After a gene duplication where both genes are retained, it predicts that original and duplicate genes diverge at clock-like rates. This prediction is usually tested for coding sequences, but can also be applied(More)
Neutralism and selectionism are extremes of an explanatory spectrum for understanding patterns of molecular evolution and the emergence of evolutionary innovation. Although recent genome-scale data from protein-coding genes argue against neutralism, molecular engineering and protein evolution data argue that neutral mutations and mutational robustness are(More)
Most duplicate genes are eliminated from a genome shortly after duplication, but those that remain are an important source of biochemical diversity. Here, I present evidence from genome-scale protein-protein interaction data, microarray expression data, and large-scale gene knockout data that this diversification is often asymmetrical: one duplicate usually(More)