CAS-MPG Partner Institute and CAS Key Laboratory for Computational Biology, Shanghai Institutes for Biological Sciences, The Chinese Academy of Sciences, Shanghai 200031, China.
J Integr Plant Biol. 2013 Feb;55(2):131-41. doi: 10.1111/j.1744-7909.2012.01184.x. Epub 2012 Dec 5.
The mechanism underlying pollen tube growth involves diverse genes and molecular pathways. Alterations in the regulatory genes or pathways cause phenotypic changes reflected by cellular morphology, which can be captured using fluorescence microscopy. Determining and classifying pollen tube morphological phenotypes in such microscopic images is key to our understanding the involvement of genes and pathways. In this context, we propose a computational method to extract quantitative morphological features, and demonstrate that these features reflect morphological differences relevant to distinguish different defects of pollen tube growth. The corresponding software tool furthermore includes a novel semi-automated image segmentation approach, allowing to highly accurately identify the boundary of a pollen tube in a microscopic image.
花粉管生长的机制涉及多种基因和分子途径。调节基因或途径的改变导致细胞形态的表型变化，这可以通过荧光显微镜捕捉到。在这些微观图像中确定和分类花粉管形态表型是我们理解基因和途径参与的关键。在这种情况下，我们提出了一种计算方法来提取定量形态特征，并证明这些特征反映了与区分不同花粉管生长缺陷相关的形态差异。相应的软件工具还包括一种新颖的半自动图像分割方法，可高度准确地识别微观图像中花粉管的边界。
