Probabilistic Modeling of Information from Images and Text in Online Journals

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DESCRIPTION (provided by applicant): The goal of this project is to build a software toolkit that will enable a biologist to create, from a collection of on-line articles, a database of protein subcellular localization information that can be queried, browsed, or used to support data-mining activities. We have developed a system, called SLIF, which can harvest fluorescence microscope images from online papers, analyze them using image-processing methods, and annotate them with information appearing in the accompanying textual description. We propose to improve and extend this system so as to produce a robust, comprehensive toolkit for extracting information about subcellular localization from the text and images found in online journals, as well as analyzing, verifying and querying the resulting body of information.