Aim: Focusing on the feature of genetic data, such as privacy, evolution, multi-measure, heterogeneity, systematicness, and so on, combing molecular biology experiments and clinical scientific issues contribute to the reestablishment of dynamic evolving molecular networks of disease, the scientific basis and informatics platform for the precise diagnosis, treatment and intelligent health management of diseases. Thus, our specific work follow the three aspects:

1. Establishing the model and platform for disease biomedical data sharing and security, such as the disease-specific ontology; the ontology-based data sharing model and the data security protection,  database and knowledge base for a series of disease, etc;
2. Establishing different omits, such as genomics, proteomics, metabonomics, microbiome, single-cell omics, physiological phenotypes, and clinical phenotypes, cheminformatics, etc,  unique ecological network models and data analysis platforms of various omits;
3. Establishing knowledge-guided biomedical and health intelligence engineering, and promoting the transformation and application of informatics in chronic disease management, hierarchical diagnosis and treatment, and personalized health management.