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Global signatures of protein binding on structured RNAs in Saccharomyces cerevisiae 被引量:7
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作者 YANG YuCheng UMETSU Jumpei LU Zhi John 《Science China(Life Sciences)》 SCIE CAS 2014年第1期22-35,共14页
Protein binding is essential to the transport,decay and regulation of almost all RNA molecules.However,the structural preference of protein binding on RNAs and their cellular functions and dynamics upon changing envir... Protein binding is essential to the transport,decay and regulation of almost all RNA molecules.However,the structural preference of protein binding on RNAs and their cellular functions and dynamics upon changing environmental conditions are poorly understood.Here,we integrated various high-throughput data and introduced a computational framework to describe the global interactions between RNA binding proteins(RBPs)and structured RNAs in yeast at single-nucleotide resolution.We found that on average,in terms of percent total lengths,~15%of mRNA untranslated regions(UTRs),~37%of canonical non-coding RNAs(ncRNAs)and^11%of long ncRNAs(lncRNAs)are bound by proteins.The RBP binding sites,in general,tend to occur at single-stranded loops,with evolutionarily conserved signatures,and often facilitate a specific RNA structure conformation in vivo.We found that four nucleotide modifications of tRNA are significantly associated with RBP binding.We also identified various structural motifs bound by RBPs in the UTRs of mRNAs,associated with localization,degradation and stress responses.Moreover,we identified>200 novel lncRNAs bound by RBPs,and about half of them contain conserved secondary structures.We present the first ensemble pattern of RBP binding sites in the structured non-coding regions of a eukaryotic genome,emphasizing their structural context and cellular functions. 展开更多
关键词 酵母RNA 结构化 蛋白质 签名 约束力 非编码RNA RNA结合蛋白 酿酒
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基于图熵的社会网络演化分析 被引量:2
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作者 郭瑞 钟宁 李文斌 《模式识别与人工智能》 EI CSCD 北大核心 2009年第3期360-365,共6页
通过图熵测度来描述在网络演化过程中网络的有序性,并在安然数据集上得出全局属性和局部属性在网络演化中有序性的不同趋势,这体现社会网络的一个主要特征,即多尺度上的不一致性.然后通过熵参与度来识别网络中的重要结点.最后,从理论上... 通过图熵测度来描述在网络演化过程中网络的有序性,并在安然数据集上得出全局属性和局部属性在网络演化中有序性的不同趋势,这体现社会网络的一个主要特征,即多尺度上的不一致性.然后通过熵参与度来识别网络中的重要结点.最后,从理论上解释全局属性和局部属性在有序性上网络演化呈现不同趋势的原因. 展开更多
关键词 社会网络 邮件网络 图熵 熵参与度 结点识别
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