Lee Insuk, Date Shailesh V, Adai Alex T, Marcotte Edward M
Center for Systems and Synthetic Biology, Institute for Molecular Biology, University of Texas at Austin, Austin, TX 78712-1064, USA.
Science. 2004 Nov 26;306(5701):1555-8. doi: 10.1126/science.1099511.
A conceptual framework for integrating diverse functional genomics data was developed by reinterpreting experiments to provide numerical likelihoods that genes are functionally linked. This allows direct comparison and integration of different classes of data. The resulting probabilistic gene network estimates the functional coupling between genes. Within this framework, we reconstructed an extensive, high-quality functional gene network for Saccharomyces cerevisiae, consisting of 4681 (approximately 81%) of the known yeast genes linked by approximately 34,000 probabilistic linkages comparable in accuracy to small-scale interaction assays. The integrated linkages distinguish true from false-positive interactions in earlier data sets; new interactions emerge from genes' network contexts, as shown for genes in chromatin modification and ribosome biogenesis.
通过重新解释实验以提供基因功能相关的数值可能性，开发了一个整合多种功能基因组数据的概念框架。这使得不同类别的数据能够直接进行比较和整合。由此产生的概率性基因网络可估计基因之间的功能耦合。在此框架内，我们为酿酒酵母重建了一个广泛、高质量的功能基因网络，该网络由4681个（约占已知酵母基因的81%）基因组成，这些基因通过约34000个概率性连接相连，其准确性与小规模相互作用检测相当。整合后的连接区分了早期数据集中的真实相互作用和假阳性相互作用；新的相互作用从基因的网络背景中浮现出来，如在染色质修饰和核糖体生物发生中的基因所示。
