A computational framework for global analysis of translation regulation

 描述（由申请人提供）：核糖体分析提供了关于翻译核糖体的数量和行为的定量信息，并给出了与实际蛋白质水平密切相关的基因表达谱。然而，核糖体分析技术尚未被广泛采用，一个主要原因是缺乏用于分析核糖体分析数据的必要计算方法。通过这个项目，我们将开发一个计算框架来解决分析核糖体分析数据中的一系列具体问题，包括数据驱动的ORF识别，纠正核糖体停滞影响的翻译措施，以及从时间序列数据估计核糖体延伸速度的概率模型。将进行具体的实验，以支持和挑战计算方法的发展，并对现有的实验技术进行重大改进，进行核糖体足迹也将开发。最终，通过完成本提案的目标，我们将采取重大步骤，使核糖体分析技术在确定细胞分子表型方面得到更广泛的应用。

 DESCRIPTION (provided by applicant): Ribosome profiling delivers quantitative information on the number and behavior of translating ribosomes, and gives profiles of gene expression much more closely linked to actual protein levels. The ribosomal profiling technology, however, is not yet widely adopted, and a major reason is that essential computational methods for analyzing ribosomal profiling data are lacking. Through this project we will develop a computational framework to address a set of specific problems in analyzing ribosomal profiling data, including data-driven ORF identification, correcting measures of translation for the influence of ribosome stalling, and a probabilistic model to estimate ribosome elongation speed from time-series data. Specific experiments will be conducted to support and challenge the development of computational methods, and major refinements to existing experimental technology for conducting ribosomal foot-printing will also be developed. Ultimately, through completing the aims of this proposal, we will take major steps in bringing ribosomal profiling technology into broader use in defining molecular phenotypes of cells.