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Single-molecule dataset (SMD): a generalized storage format for raw and processed single-molecule data

机译:单分子数据集(SMD):原始和处理后的单分子数据的通用存储格式

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摘要

BackgroundSingle-molecule techniques have emerged as incisive approaches for addressing a wide range of questions arising in contemporary biological research [Trends Biochem Sci 38:30–37, 2013; Nat Rev Genet 14:9–22, 2013; Curr Opin Struct Biol 2014, 28C:112–121; Annu Rev Biophys 43:19–39, 2014]. The analysis and interpretation of raw single-molecule data benefits greatly from the ongoing development of sophisticated statistical analysis tools that enable accurate inference at the low signal-to-noise ratios frequently associated with these measurements. While a number of groups have released analysis toolkits as open source software [J Phys Chem B 114:5386–5403, 2010; Biophys J 79:1915–1927, 2000; Biophys J 91:1941–1951, 2006; Biophys J 79:1928–1944, 2000; Biophys J 86:4015–4029, 2004; Biophys J 97:3196–3205, 2009; PLoS One 7:e30024, 2012; BMC Bioinformatics 288 11(8):S2, 2010; Biophys J 106:1327–1337, 2014; Proc Int Conf Mach Learn 28:361–369, 2013], it remains difficult to compare analysis for experiments performed in different labs due to a lack of standardization.
机译:背景技术单分子技术已成为解决当代生物学研究中出现的广泛问题的敏锐方法[Trends Biochem Sci 38:30-37,2013; Nat Rev Genet 14:9–22,2013; Curr Opin Struct Biol 2014,28C:112–121; 2014年生物物理学年鉴43:19–39]。原始的单分子数据的分析和解释将受益于不断发展的复杂统计分析工具,这些工具可在经常与这些测量相关的低信噪比下进行准确推断。尽管许多小组已将分析工具包作为开源软件发布[J Phys Chem B 114:5386–5403,2010; Biophys J 79:1915–1927,2000; Biophys J 91:1941–1951,2006; Biophys J 79:1928-1944,2000; Biophys J 86:4015-4029,2004; Biophys J 97:3196-3205,2009; PLoS One 7:e30024,2012; BMC Bioinformatics 288 11(8):S2,2010; Biophys J 106:1327-1337,2014; Proc Int Conf Mach Learn 28:361–369,2013],由于缺乏标准化,因此很难比较在不同实验室进行的实验的分析结果。

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