  The automated assembly and extension of dynamic network models using
information extracted from literature are challenging due to the amount and
inconsistency in published literature. Recently, efforts have been made to
automatically and efficiently assemble the information extracted from
literature 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-cell
differentiation as compared against a number of predefined system properties.
