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Addressing the unmet need for visualizing conditional random fields in biological data

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Addressing the unmet need for visualizing conditional random fields in biological data

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The biological world is replete with phenomena that appear to be ideally modeled and analyzed by one archetypal statistical framework - the Graphical Probabilistic Model (GPM). The structure of GPMs is a uniquely good match for biological problems that range from aligning sequences to modeling the genome-to-phenome relationship.

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