Analysis of spatial point patterns in nuclear biology.

Analysis of spatial point patterns in nuclear biology.
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分析核生物学中的空间点模式。

DOI:
10.1371/journal.pone.0036841
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发表时间:
2012
期刊:
影响因子:
3.7
通讯作者:
Freemont PS
Freemont PS
中科院分区:
综合性期刊3区
文献类型:
--
作者:
Weston DJ;Adams NM;Russell RA;Stephens DA;Freemont PS

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在确定核物体的空间排列是否以及在多大程度上影响核功能方面,细胞生物学有相当大的兴趣。解决这一问题的一种常见方法是分析使用某种形式的荧光显微镜产生的图像集合。我们假设这些图像已经被成功地进行了预处理,并且核边界内的感兴趣对象的空间点模式表示是可用的。通常在这些情况下,每个核的对象数量很少,这对标准分析程序证明模式中存在空间偏好的能力产生了影响。在这些空间点模式中寻找结构大致有两种常见的方法。首先,单独分析每个图像的空间点图案,或者第二,执行简单的归一化并聚集图案。在这篇文章中,我们使用从预定义的点过程中提取的合成空间点模式来演示使用这些技术将模式与完全的空间随机性区分开来是多么困难,因此在核物体的排列中很容易错过有趣的空间偏好。这个问题的影响也在与哺乳动物成纤维细胞中PML核体构型相关的数据上得到了说明。
There is considerable interest in cell biology in determining whether, and to what extent, the spatial arrangement of nuclear objects affects nuclear function. A common approach to address this issue involves analyzing a collection of images produced using some form of fluorescence microscopy. We assume that these images have been successfully pre-processed and a spatial point pattern representation of the objects of interest within the nuclear boundary is available. Typically in these scenarios, the number of objects per nucleus is low, which has consequences on the ability of standard analysis procedures to demonstrate the existence of spatial preference in the pattern. There are broadly two common approaches to look for structure in these spatial point patterns. First a spatial point pattern for each image is analyzed individually, or second a simple normalization is performed and the patterns are aggregated. In this paper we demonstrate using synthetic spatial point patterns drawn from predefined point processes how difficult it is to distinguish a pattern from complete spatial randomness using these techniques and hence how easy it is to miss interesting spatial preferences in the arrangement of nuclear objects. The impact of this problem is also illustrated on data related to the configuration of PML nuclear bodies in mammalian fibroblast cells.
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影响因子: --
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DOI: 10.1016/j.ecolmodel.2011.10.005
发表时间: 2011-12-10
影响因子: 3.1
作者:
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