Please use this identifier to cite or link to this item: https://doi.org/10.1007/978-3-642-16001-1_25
Title: Quantification of cytoskeletal protein localization from high-content images
Authors: Zhu, S.
Matsudaira, P. 
Welsch, R.
Rajapakse, J.C.
Keywords: Colocalization
cytoskeletal proteins
cytoskeleton
subcellular localization
Issue Date: 2010
Citation: Zhu, S.,Matsudaira, P.,Welsch, R.,Rajapakse, J.C. (2010). Quantification of cytoskeletal protein localization from high-content images. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 6282 LNBI : 289-300. ScholarBank@NUS Repository. https://doi.org/10.1007/978-3-642-16001-1_25
Abstract: Cytoskeletal proteins function as dynamic and complex components in many aspects of cell physiology and the maintenance of cell structure. However, very little is known about the coordinated system of these proteins. The knowledge of subcellular localization of proteins is crucial for understanding how proteins function within a cell. We present a framework for quantification of cytoskeletal protein localization from high-content microscopic images. Analyses of high content images of cells transfected by cytoskeleton genes involve individual cell segmentation, intensity transformation of subcellular compartments, protein segmentation based on correlation coefficients, and colocalization quantification of proteins in subcellular components. By quantifying the abundance of proteins in different compartments, we generate colocalization profiles that give insights into the functions of different cytoskeletal proteins. © 2010 Springer-Verlag.
Source Title: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
URI: http://scholarbank.nus.edu.sg/handle/10635/102230
ISBN: 364216000X
ISSN: 03029743
DOI: 10.1007/978-3-642-16001-1_25
Appears in Collections:Staff Publications

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