European Bioinformatics Institute, Cambridge, UK.
Nat Methods. 2010 Mar;7(3 Suppl):S56-68. doi: 10.1038/nmeth.1436.
High-throughput studies of biological systems are rapidly accumulating a wealth of 'omics'-scale data. Visualization is a key aspect of both the analysis and understanding of these data, and users now have many visualization methods and tools to choose from. The challenge is to create clear, meaningful and integrated visualizations that give biological insight, without being overwhelmed by the intrinsic complexity of the data. In this review, we discuss how visualization tools are being used to help interpret protein interaction, gene expression and metabolic profile data, and we highlight emerging new directions.
高通量生物系统研究正在迅速积累大量的“组学”规模数据。可视化是分析和理解这些数据的关键方面，现在用户有许多可视化方法和工具可供选择。挑战在于创建清晰、有意义和集成的可视化效果，以提供生物学见解，而不会被数据的固有复杂性所淹没。在这篇综述中，我们讨论了可视化工具如何帮助解释蛋白质相互作用、基因表达和代谢谱数据，并强调了新兴的新方向。
