Determination of the functions of all expressed proteins represents one of the major upcoming challenges in computational molecular biology. Since subcellular location plays a crucial role in protein function, the ava...
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Describes a method of classifying cellular protein localization patterns based on their appearance in fluorescence lightmicroscope images. Images depicting cellular protein localization were obtained using immunofluo...
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Describes a method of classifying cellular protein localization patterns based on their appearance in fluorescence lightmicroscope images. Images depicting cellular protein localization were obtained using immunofluorescence microscopy. After collection, the images were processed and subject to feature extraction. Zernike moments were calculated for each image and used as inputs to one of two classification schemes: a classification tree or a neural network. Of the two classifiers, the neural network demonstrated better performance, correctly classifying 84% of previously unseen images. This work has application as a novel approach to protein description, as a means of automating microscopes, and as part of a new approach to gene discovery.
The widespread availability of automated fluorescence microscope systems has led to an explosion in the acquisition of digital images by biologists. This has created a need for computer applications that automate the ...
The widespread availability of automated fluorescence microscope systems has led to an explosion in the acquisition of digital images by biologists. This has created a need for computer applications that automate the analysis of these images and an opportunity to develop new approaches to classical problems. An example is the determination of the subcellular location of a protein from immunofluorescence images (or, more recently, images of GFP fluorescence). Current practice is to compare such images to mental images that a cell biologist has developed over time, and to reach a tentative conclusion about the structure (i.e., organelle) that a protein is found in. Since this determination is subjective, it often must be followed up by double labeling with a marker protein from the suspected *** an initial exploration of the feasibility of automating the determination of subcellular location, we developed a system that is able to classify the localization patterns characteristic of five cellular molecules (proteins and DNA) in Chinese Hamster Ovary (CHO) cells. Images were acquired on an epifluorescence microscope after the cells had been fixed, permeabilized, and labeled with appropriate fluorescent reagents (usually antibodies conjugated to fluorescent dyes). The labels used were directed against a Golgi protein, a lysosomal protein, a nuclear protein, a cytoskeletal protein, and DNA.
By measuring the orientation of colloidal doublets suspended in water under the opposing alignment forces of gravity and electrophoresis, we observed tangential forces between nontouching particles. We found a new phe...
By measuring the orientation of colloidal doublets suspended in water under the opposing alignment forces of gravity and electrophoresis, we observed tangential forces between nontouching particles. We found a new phenomenon of time-dependent switching between “slipping” (no tangential force) and “sticking” (tangential forces producing rigid-body behavior of the doublet) for heterodoublets of silica/polystyrene. Tangential forces between particle surfaces across a fluid gap and their transient nature are important to the dynamics of colloidal suspensions and the evolution of floc morphology.
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