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Location proteomics - Building subcellular location trees from high resolution 3D fluorescence microscope images of randomly-tagged proteins

机译：位置蛋白质组学 - 从高分辨率3D荧光显微镜图像中随机标记蛋白质构建亚细胞定位树

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Xiang Chen Meel; Xiang Chen; Meel Velliste; Shmuel Weinstein; Jonathan W. Jarvik; Robert F. Murphy;
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年度 2008
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1. Automated interpretation of subcellular patterns in fluorescence microscope images for location proteomics [J] . Chen X, Velliste M, Murphy RF Cytometry, Part A: the journal of the International Society for Analytical Cytology . 2006,第7期

机译：荧光显微镜图像中亚细胞图案的自动解释蛋白质组学
2. Robust Numerical Features for Description and Classification of Subcellular Location Patterns in Fluorescence Microscope Images [J] . ROBERT F. MURPHY, MEEL VELLISTE, GREGORY PORRECA Journal of VLSI signal processing . 2003,第3期

机译：用于描述和分类荧光显微镜图像中亚细胞定位模式的鲁棒数值特征
3. Determining the subcellular location of new proteins from microscope images using local features [J] . Coelho Luis Pedro, Kangas Joshua D., Naik Armaghan W., Bioinformatics . 2013,第18期

机译：使用局部特征从显微镜图像确定新蛋白质的亚细胞位置
4. Location proteomics - Building subcellular location trees from high resolution 3D fluorescence microscope images of randomly-tagged proteins [C] . Xiang Chen, Meel Velliste, Shmuel Weinstein, Conference on Manipulation and Analysis of Biomolecules, Cells, and Tissues Jan 28-29, 2003 San Jose, California, USA . 2003

机译：定位蛋白质组学-从高分辨率3D荧光显微镜图像中随机标记的蛋白质构建亚细胞定位树
5. Automated analysis of the subcellular location of proteins in NIH3T3 and CaCo2 cells using fluorescence microscope images. [D] . Garcia Osuna, Elvira. 2007

机译：使用荧光显微镜图像自动分析NIH3T3和CaCo2细胞中蛋白质的亚细胞位置。
6. Automated Interpretation of Subcellular Patterns in Fluorescence Microscope Images for Location Proteomics [O] . Xiang Chen, Meel Velliste, Robert F. Murphy -1

机译：定位蛋白组学在荧光显微镜图像中亚细胞模式的自动解释
7. Automated interpretation of subcellular patterns in fluorescence microscope images for location proteomics [O] . Xiang Chen, Meel Velliste, Robert F. Murphy 2011

机译：用于位置蛋白质组学的荧光显微镜图像中亚细胞模式的自动解释

Location proteomics - Building subcellular location trees from high resolution 3D fluorescence microscope images of randomly-tagged proteins

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