Gene Regulation Network (GRN) is a graphical representation of the relationship between molecular mechanisms and cellular behavior in system biology. This paper examines the extraction of GRN from biological literatures using text mining techniques. The study proposes two independent methods first, a syntactic method and a semantic method in text mining, to extract biological events from the unstructured text. The paper presents the performance of the two methods and then experiments with the combined strategy to construct a gene regulation network from texts. The results show that the graph-based approach obtains a better result on event extraction and produces a much better regulation network than the semantic analysis method. The combination of the two approaches has yet a much slightly better result than that with the individual approach. This exhilarates us to find more future directions in the biological event extraction research.