With the success of the human genomic project, the amount of experimental data is increasing rapidly. In the post-genomic era, the focus is now shifting to the so called "from the sequence to the function", i.e., in addition to completing genome sequences, it is possible to learn about gene expression patterns and protein interactions on the genomic scale. Description and analysis of complex Genetic Regulatory Networks (GRN) is a critical problem for biologists to understand genetic regulatory mechanism. Most of existing methods ignore the synergistic effects observed widely in biologic systems. Thus there should be some errors between the predictions of the model and the actual biologic behaviors. To address this problem, a new quantitative analysis approach for genetic regulatory networks was proposed in the context of Hybrid Functional Petri Net (HFPN). Firstly, basic theory of GRN and HFPN was presented briefly. Petri-net-based models have been widely adopted for studying biological systems since Petri net has graphical modeling representation and strict mathematic background. In GRN, the combined effect of transcription factors to induce or repress gene transcription is usually different from the simple sum of their individual effects. This is so called Synergistic effect. Two kinds of new elements, logic places and logic transitions were introduced to describe the logic rules in GRN and the synergy between transcription factors. It was decided to extend existing tools instead of writing new software in order to have more time for the experimental part of this project. A Petri Net Workbench was developed based on the Open Source project the Petri Net Kernel (PNK) and the Systems Biology Workbench (SBW) during this project. The Petri Net Workbench was extended by the following features: the extended definition of Hybrid Functional Petri Net, the Ordinary Differential Equations (ODEs) solver, Systems Biology Markup Language (SBML) support and time course simulation. Finally, a Petri net model for the genetic regulatory network of the sea urchin endo16 gene was developed base on the GRN model published in literature and a list of quantitative outputs for different mutations was predicted. The analysis result corresponded to the experimental data published in literature properly and demonstrated the correctness of the Petri net model. It demonstrated how Hybrid Functional Petri net analysis techniques can be applied to Genetic Regulatory Networks. The new concepts of logic places and logic transitions had been proven to be useful for describe the logic rules in GRN and the synergy between transcription factors.