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Ribo-seq on K562 and HepG2 cells. Ribo-seq on K562 and HepG2 cells

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NIAID Data Ecosystem2026-03-11 收录
下载链接:
https://www.ncbi.nlm.nih.gov/bioproject/PRJNA529885
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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. Overall design: 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:
2019-03-29
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