Elvira Osuna-Highley

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MOTIVATION Evaluation of previous systems for automated determination of subcellular location from microscope images has been done using datasets in which each location class consisted of multiple images of the same representative protein. Here, we frame a more challenging and useful problem where previously unseen proteins are to be classified. RESULTS(More)
Current cell culture practices are dependent upon human operators and remain laborious and highly subjective, resulting in large variations and inconsistent outcomes, especially when using visual assessments of cell confluency to determine the appropriate time to subculture cells. Although efforts to automate cell culture with robotic systems are underway,(More)
MOTIVATION Image analysis, machine learning and statistical modeling have become well established for the automatic recognition and comparison of the subcellular locations of proteins in microscope images. By using a comprehensive set of features describing static images, major subcellular patterns can be distinguished with near perfect accuracy. We now(More)
To test the feasibility of localized intravaginal therapy directed to neighboring lymph nodes, the transport of quantum dots across the vaginal wall was investigated. Quantum dots instilled into the mouse vagina were transported across the vaginal mucosa into draining lymph nodes, but not into distant nodes. Most of the particles were transported to the(More)
Location proteomics is concerned with the systematic analysis of the subcellular location of proteins. In order to perform comprehensive analysis of all protein location patterns, automated methods are needed. With the goal of extending automated subcellular location pattern analysis methods to high resolution images of tissues, 3D confocal microscope(More)
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