Important numerical features for novel endoplasmic reticulum genes classification of protein localizations in micrographs

Han-Wei Dan, Chung-Chih Lin, Y.‐S. Tsai
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Abstract

Localization of proteins ties closely with the protein functions-the disorder of protein delivering can cause misfunction of the protein and genetic diseases. The analysis of micrographs can help to understand the distribution of proteins in the cell. ER protein's images analysis leads the researches to know that the same protein localization means the proteins have same function, and to understand the phylogenetic relationship by image's morphologies. This research uses SDA to find the best combination of features from original, skeletonized and brighter area images, which then utilized in SVM classification. The accuracy of this system can achieve 74% for the images acquired by the same hardware equipment.
新型内质网基因在显微图像中蛋白质定位分类的重要数值特征
蛋白质的定位与蛋白质的功能密切相关,蛋白质传递的紊乱会导致蛋白质的功能失调和遗传性疾病。显微照片的分析有助于了解细胞中蛋白质的分布。内质网蛋白的图像分析使研究人员认识到相同的蛋白质定位意味着相同的蛋白质具有相同的功能,并通过图像的形态学来了解它们的系统发育关系。本研究利用SDA从原始图像、骨架图像和较亮区域图像中寻找最佳的特征组合,然后将其用于SVM分类。对于相同硬件设备采集的图像,该系统的精度可达到74%。
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