Probabilistic inference of molecular networks from noisy data sources


Information on molecular networks, such as networks of interacting proteins, comes from diverse sources that contain remarkable differences in distribution and quantity of errors. Here, we introduce a probabilistic model useful for predicting protein interactions from heterogeneous data sources. The model describes stochastic generation of protein-protein… (More)
DOI: 10.1093/bioinformatics/bth061


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