Data intensive disciplines, such as life sciences and medicine, are promoting vivid research activities in the area of databases. Modern technologies, such as high-throughput mass-spectrometry and sequencing, micro-arrays, high-resolution imaging, etc., produce enormous and continuously increasing amounts of data. Huge public databases provide access to aggregated and consolidated information on genome and protein sequences, biological pathways, diseases, anatomy atlases, and scientific literature. There has never been more potentially available information to study biomedical systems, ranging from single cells to complete organisms. However, it is a non-trivial task to transform the vast amount of biomedical data into actionable information, triggering scientific progress and supporting patient management.
Major biomedical application scenarios for research in the database community include, but are not limited to:
Systems biology
Genomics, proteomics, and metabolomics
Genome-wide association studies
Drug target discovery and personalized medicine
Neuroscience and neuroinformatics
Electronic patient records
Patient monitoring
Surgery planning and support
Other relevant applications
Various emerging database technologies for coping with the challenges of these application scenarios have been developed and are an active area of research in information technology:
Administration of vast amounts of data
Integration of heterogeneous data sources
Federated and distributed databases
Data warehouses
Data mining techniques such as classification, clustering, association rule mining, etc.
Decision support systems
Information and image retrieval
Signal processing and streaming databases
Privacy protection and data security
Data quality assurance
Process management and collaborative work
User interfaces and visualization
Interoperability and standardization
Other relevant applications
08月28日
2017
08月31日
2017
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