首页> 外文会议>Evolutionary computation, machine learning and data mining in bioinformatics. >Measuring Gene Expression Noise in Early Drosophila Embryos: The Highly Dynamic Compartmentalized Micro-environment of the Blastoderm Is One of the Main Sources of Noise
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Measuring Gene Expression Noise in Early Drosophila Embryos: The Highly Dynamic Compartmentalized Micro-environment of the Blastoderm Is One of the Main Sources of Noise

机译:测量早期果蝇胚胎中的基因表达噪声:高动态区室的胚盘微环境是噪声的主要来源之一。

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Fluorescence imaging has become a widely used technique for quantitatively measuring mRNA or protein expression. The first measurements were on gene expression noise in bacteria and yeast. The relative biological and physicochemical simplicity of these single cells encouraged a number of groups to try similar approaches in multicellular organisms. Such work has been primarily on whole Drosophila embryos, where the genes forming the body plan are very well understood. The numerous sources of noise in complex embryonic tissues are a major challenge for characterizing gene expression noise. Here, we present our approach for first separating experimental from biological noise, followed by distinguishing sources of biological noise. We decompose raw signal into trend and residual noise using Singular Spectrum Analysis. We demonstrate our statistical techniques on the Drosophila Hunchback protein pattern. We show that the 'texture noise', arising from the pre-cellular compartmentalization of the embryo surface, which is highly dynamic in time, is a major component of total biological noise, and can exceed gene transcription/translation noise.
机译:荧光成像已成为定量测量mRNA或蛋白质表达的一种广泛使用的技术。最初的测量是关于细菌和酵母中的基因表达噪声。这些单细胞的相对生物学和理化简单性鼓励了许多小组在多细胞生物中尝试类似的方法。这项工作主要针对整个果蝇胚胎,在那里人们对形成人体计划的基因非常了解。复杂胚胎组织中的多种噪声源是表征基因表达噪声的主要挑战。在这里,我们介绍了首先将实验噪声与生物噪声分离,然后区分生物噪声源的方法。我们使用奇异频谱分析将原始信号分解为趋势和残留噪声。我们证明了我们的果蝇驼背蛋白质模式的统计技术。我们表明,由胚胎表面的前细胞区室化引起的“纹理噪声”在时间上是高度动态的,是总生物噪声的主要组成部分,并且可以超过基因转录/翻译噪声。

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