Parametric Bayesian priors and better choice of negative examples improve protein function prediction

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Parametric Bayesian priors and better choice of negative examples improve protein function prediction

MOTIVATION Computational biologists have demonstrated the utility of using machine learning methods to predict protein function from an integration of multiple genome-wide data types. Yet, even the best performing function prediction algorithms rely on heuristics for important components of the algorithm, such as choosing negative examples (proteins without a given function) or determining key ...

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ژورنال

عنوان ژورنال: Bioinformatics

سال: 2013

ISSN: 1460-2059,1367-4803

DOI: 10.1093/bioinformatics/btt110