
pmid: 15245901
Synthetic biology is advancing rapidly as biologists, physicists and engineers are combining their efforts to understand and program cell function. By characterizing isolated genetic components or modules, experimentalists have paved the way for more quantitative analyses of genetic networks. A recent paper presents a method of computational, or in silico, evolution in which a set of components can evolve into networks that display desired behaviors. An integrated approach that includes a strategy of in silico design by evolution, together with efforts exploiting directed evolution in vivo, is likely to be the next step in the evolution of synthetic biology.
Evolution, Molecular, Gene Expression Regulation, Protein Interaction Mapping, Animals, Humans, Computer Simulation, Models, Biological, Algorithms, Cell Physiological Phenomena, Signal Transduction
Evolution, Molecular, Gene Expression Regulation, Protein Interaction Mapping, Animals, Humans, Computer Simulation, Models, Biological, Algorithms, Cell Physiological Phenomena, Signal Transduction
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 15 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
