摘要翻译:
DNA分子的互补链在被力拉伸时可以分离;解压缩信号与序列的基本内容相关,但受热噪声和仪器噪声的影响。我们在这里考虑一种理想的情况,即打开事件以非常好的时间分辨率(非常大的带宽)已知,并研究如何从解压缩数据中重建序列。我们的方法依赖于统计贝叶斯推理和维特比译码算法的使用。在蒙特卡罗生成的数据上对性能进行了数值研究,并对其进行了分析。我们展示了如何利用同一分子的多次解拉链来提高预测的质量,并分析计算了所需解拉链的数量作为带宽、序列含量和解拉链弹性参数的函数。
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英文标题:
《Inferring DNA sequences from mechanical unzipping data: the
large-bandwidth case》
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作者:
Valentina Baldazzi (LPS), Serena Bradde (LPS), Simona Cocco (LPS),
Enzo Marinari, Remi Monasson (LPTENS)
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最新提交年份:
2007
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分类信息:
一级分类:Quantitative Biology 数量生物学
二级分类:Biomolecules 生物分子
分类描述:DNA, RNA, proteins, lipids, etc.; molecular structures and folding kinetics; molecular interactions; single-molecule manipulation.
DNA、RNA、蛋白质、脂类等;分子结构与折叠动力学;分子相互作用;单分子操作。
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一级分类:Physics 物理学
二级分类:Statistical Mechanics 统计力学
分类描述:Phase transitions, thermodynamics, field theory, non-equilibrium phenomena, renormalization group and scaling, integrable models, turbulence
相变,热力学,场论,非平衡现象,重整化群和标度,可积模型,湍流
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英文摘要:
The complementary strands of DNA molecules can be separated when stretched apart by a force; the unzipping signal is correlated to the base content of the sequence but is affected by thermal and instrumental noise. We consider here the ideal case where opening events are known to a very good time resolution (very large bandwidth), and study how the sequence can be reconstructed from the unzipping data. Our approach relies on the use of statistical Bayesian inference and of Viterbi decoding algorithm. Performances are studied numerically on Monte Carlo generated data, and analytically. We show how multiple unzippings of the same molecule may be exploited to improve the quality of the prediction, and calculate analytically the number of required unzippings as a function of the bandwidth, the sequence content, the elasticity parameters of the unzipped strands.
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PDF链接:
https://arxiv.org/pdf/704.2547