five

Ribo-seq on K562 and HepG2 cells

收藏
NIAID Data Ecosystem2026-03-11 收录
下载链接:
https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE129061
下载链接
链接失效反馈
官方服务:
资源简介:
Deep sequencing methods have matured to comprehensively detect the full set of transcribed loci, but there is a gap to determine the function of the resulting highly complex transcriptomes. To this end, we have developed a new approach named ORFquant to annotate and quantify translation at the single open reading frame (ORF) level using Ribo-seq data. After RNase I footprinting in CHX-containing lysis buffer, RNA fragments around 29nt were isolated and subjected to rRNA depletion using RiboZero.
创建时间:
2020-07-27
5,000+
优质数据集
54 个
任务类型
进入经典数据集
二维码
社区交流群

面向社区/商业的数据集话题

二维码
科研交流群

面向高校/科研机构的开源数据集话题

数据驱动未来

携手共赢发展

商业合作