Institute for Systems Biology, Seattle, WA, United States.
Curr Opin Biotechnol. 2012 Aug;23(4):598-603. doi: 10.1016/j.copbio.2011.12.005. Epub 2011 Dec 28.
Biological systems can now be understood in comprehensive and quantitative detail using systems biology approaches. Putative genome-scale models can be built rapidly based upon biological inventories and strategic system-wide molecular measurements. Current models combine statistical associations, causative abstractions, and known molecular mechanisms to explain and predict quantitative and complex phenotypes. This top-down 'reverse engineering' approach generates useful organism-scale models despite noise and incompleteness in data and knowledge. Here we review and discuss the reverse engineering of biological systems using top-down data-driven approaches, in order to improve discovery, hypothesis generation, and the inference of biological properties.
现在，通过系统生物学方法，可以全面、定量地了解生物系统。可以根据生物目录和系统范围的分子策略性测量快速构建假定的基因组规模模型。目前的模型结合了统计关联、因果抽象和已知的分子机制，以解释和预测定量和复杂的表型。这种自上而下的“反向工程”方法可以生成有用的生物体规模模型，尽管数据和知识中存在噪声和不完整性。在这里，我们回顾和讨论了使用自上而下的数据驱动方法对生物系统进行反向工程，以提高发现、假设生成和推断生物特性的能力。
