生物
核糖体分析
计算生物学
RNA序列
转录组
剧目
补语(音乐)
核糖体
集合(抽象数据类型)
翻译(生物学)
基因
遗传学
计算机科学
生物信息学
核糖核酸
基因表达
信使核糖核酸
声学
物理
表型
互补
程序设计语言
作者
Lorenzo Calviello,Uwe Ohler
标识
DOI:10.1016/j.tig.2017.08.003
摘要
By mapping the positions of millions of translating ribosomes in the cell, ribosome profiling (Ribo-seq) has established its role as a powerful tool to study gene expression. Several laboratories have introduced modifications to the experimental protocol and expanded the repertoire of biochemical methods to study translation transcriptome-wide. However, the diversity of protocols highlights a need for standardization. At the same time, different computational analysis strategies have used Ribo-seq data to identify the set of translated sequences with high confidence. In this review we present an overview of such methodologies, outlining their assumptions, data requirements, and availability. At the interface between RNA and proteins, Ribo-seq can complement data from multiple omics approaches, zooming in on the central role of translation in the molecular cell.
科研通智能强力驱动
Strongly Powered by AbleSci AI