The rapid advances in high-throughput technologies have facilitated the collection of multilevel omics data. The increasing volume of multilevel omics data continues to create larger and more complex datasets which are publicly available and can be used to generate disease-associated biological networks and to identify potential therapeutic targets within the networks. Further progress in computational methodology combined with improved disease models will facilitate the prioritization of therapeutic targets in the networks. The integration of public omics database, bioinformatics tools, and disease models can provide a strong foundation for deciphering the complex mechanism of various diseases and for data-driven drug discovery. In this symposium, I would like to demonstrate some examples of how the integrative approaches using public omics databases and animal disease models can be exploited to identify potential therapeutic targets for various disorders.