【摘 要】
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Ribosome stalling is manifested by the local accumulation of ribosomes at specific codon positions of mRNAs.Here,we present ROSE,a deep learning framework to analyze high-throughput ribosome profiling
【出 处】
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第二届中国计算机学会生物信息学会议
论文部分内容阅读
Ribosome stalling is manifested by the local accumulation of ribosomes at specific codon positions of mRNAs.Here,we present ROSE,a deep learning framework to analyze high-throughput ribosome profiling data and estimate the probability of a ribosome stalling event occurring at each genomic location.Extensive cross validation tests demonstrated that ROSE possessed higher prediction accuracy than conventional prediction models,with an increase in AUROC by up to 18.4%.In addition,genome-wide statistical analyses showed that ROSE predictions can be well correlated with diverse putative regulatory factors of ribosome stalling.
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