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The automated assembly and extension of dynamic network models usinginformation extracted from literature are challenging due to the amount andinconsistency in published literature. Recently, efforts have been made toautomatically and efficiently assemble the information extracted fromliterature into models. In this review, we summarize the basic concept,performance, advantages, and limitations of five automated extension methods.Each method was tested for its ability to reconstruct a model of T-celldifferentiation as compared against a number of predefined system properties.

New advances in the automation of context-aware information selection and guided model assembly