1. Genomic data: Genomics studies the sequence, variation and function of the human genome, which requires a lot of data for analysis and interpretation. Genomics data include gene sequence, single nucleotide variation (SNV), insertion and deletion (INDEL), copy number variation (CNV) and so on.
2. protein omics data: protein omics studies the expression, modification and interaction of protein, which can also produce a lot of data. Protein omics data include mass spectrometry data, protein sequence, interaction and so on.
3. Clinical data: Clinical data includes demographic information, medical history, diagnosis, treatment, curative effect and follow-up of patients. These data usually exist in the form of electronic health records (EHR) and health care databases.
4. Imaging data: Imaging data includes medical images, such as X-rays, CT scans, MRI and ultrasound. These image data can provide information about the structure and function of patients.
5. Environment and exposure data: These data include patients' environmental factors, living habits, exposure to chemicals or physical factors, etc. These factors may have an impact on the development and prognosis of the disease. Health-related biomarker data: These data include blood biomarkers, physiological parameters and so on, which can provide information about individual health status.
The role of biomedical big data
1. Disease prevention and control: By comprehensively analyzing the genome, living habits and environmental factors of large-scale population, the disease risk of individuals or groups can be predicted, which is helpful to take targeted preventive measures.
2. Precise medical care: Through in-depth excavation of patients' genome, clinical data and pathological information, we can provide patients with personalized diagnosis and treatment programs, improve treatment effects and reduce side effects. Drug research and development: through the analysis of biomedical big data, the process of new drug research and development can be accelerated, potential drug targets can be found, and the efficiency and success rate of drug research and development can be improved.
3. Public health monitoring: through real-time monitoring and analysis of public health data such as epidemic trend of diseases and vaccination, public health incidents can be found and responded to in time to ensure public health. Scientific research cooperation and exchange: the sharing and exchange of biomedical big data can promote scientific research cooperation on a global scale and promote the progress of medical science and technology.