Analysis of Ribosome Stalling and Translation Elongation Dynamics by Deep Learning-Reference-Cited by-同舟云学术

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Analysis of Ribosome Stalling and Translation Elongation Dynamics by Deep Learning

Published:2017-09 Issue:3 Volume:5 Page:212-220.e6
ISSN:2405-4712
Container-title:Cell Systems
language:en
Short-container-title:Cell Systems

Author:

Zhang Sai,Hu Hailin,Zhou Jingtian,He Xuan,Jiang Tao,Zeng Jianyang

Funder

National Natural Science Foundation of China

US National Science Foundation

China's Youth 1000-Talent Program

Beijing Advanced Innovation Center for Structural Biology

Publisher

Elsevier BV

Subject

Cell Biology,Histology,Pathology and Forensic Medicine

Reference81 articles.

1. Defining the specificity of cotranslationally acting chaperones by systematic analysis of mRNAs associated with ribosome-nascent chain complexes;Alamo;PLoS Biol.,2011

2. Predicting the sequence specificities of DNA-and RNA-binding proteins by deep learning;Alipanahi;Nat. Biotechnol.,2015

3. Basic local alignment search tool;Altschul;J. Mol. Biol.,1990

4. Accounting for biases in riboprofiling data indicates a major role for proline in stalling translation;Artieri;Genome Res.,2014

5. FMRP targets distinct mRNA sequence elements to regulate protein expression;Ascano;Nature,2012

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