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With the introduction of sensitive and fast electronic imaging devices and the development of biological methods to tag proteins of interest by green fluorescent proteins (GFP), it has now become critical to develop automatic quantitative data analysis tools to study the live cell dynamics at subcellular level. In this paper, a sequential Monte Carlo (SMC) method to track variable number of multiple...
In recent years, unsupervised gene (feature) selection has become an integral part of microarray analysis because of the large number of genes and complexity in biological systems. Principal components analysis (PCA) is one of the approaches which has been applied, even though principal components (PCs) have no clear physical meanings. In this paper, we present a PCA based feature selection within...
Tagging and tracking protein molecules with the help of laser scanning confocal microscope (LSCM) is a key to better understanding of proteomics in diverse aspects. One challenge of tracking multiple green fluorescent protein (GFP) clusters is how to deal with the interaction between multiple objects, namely splitting and merging. In this paper, we propose a framework to track multiple GFP clusters...
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