Dopazo Joaquín
Department of Bioinformatics, and Functional Genomics Node (INB), Centro de Investigación Príncipe Felipe (CIPF), Valencia, Spain.
OMICS. 2006 Fall;10(3):398-410. doi: 10.1089/omi.2006.10.398.
Over the past few years, due to the popularisation of high-throughput methodologies such as DNA microarrays, the possibility of obtaining experimental data has increased significantly. Nevertheless, the interpretation of the results, which involves translating these data into useful biological knowledge, still remains a challenge. The methods and strategies used for this interpretation are in continuous evolution and new proposals are constantly arising. Initially, a two-step approach was used in which genes of interest were initially selected, based on thresholds that consider only experimental values, and then in a second, independent step the enrichment of these genes in biologically relevant terms, was analysed. For different reasons, these methods are relatively poor in terms of performance and a new generation of procedures, which draw inspiration from systems biology criteria, are currently under development. Such procedures, aim to directly test the behaviour of blocks of functionally related genes, instead of focusing on single genes.
在过去几年中，由于DNA微阵列等高通量方法的普及，获取实验数据的可能性显著增加。然而，将这些数据转化为有用的生物学知识的结果解读，仍然是一项挑战。用于这种解读的方法和策略在不断发展，新的提议也不断涌现。最初，采用了两步法，首先基于仅考虑实验值的阈值选择感兴趣的基因，然后在第二步独立步骤中分析这些基因在生物学相关术语中的富集情况。由于不同原因，这些方法在性能方面相对较差，目前正在开发新一代从系统生物学标准中汲取灵感的程序。此类程序旨在直接测试功能相关基因块的行为，而不是专注于单个基因。
