Abstract: Biomedical research is now generating large amounts of data, ranging from clinical test results to microarray gene expression profiles. The scale and complexity of these datasets give rise to substantial challenges in data management and analysis. It is highly desirable that data warehousing and online analytical processing technologies can be applied to biomedical data integration and mining. The major difficulty probably lies in the task of capturing and modelling diverse biological objects and their complex relationships. This paper describes multidimensional data modelling for biomedical data warehouse design. Since the conventional models such as star schema appear to be insufficient for modelling clinical and genomic data, we develop a new model called BioStar schema. The new model can capture the rich semantics of biomedical data and provide greater extensibility for the fast evolution of biological research methodologies. Keywords: clinical and genomic data integration; multidimensional modelling; data warehouse design. Reference to this paper should be made as follows: Wang, L., Zhang, A. and Ramanathan, M. (xxxx) 'BioStar models of clinical and genomic data for biomedical data warehouse design', Int.
REF is a biomedical data warehouse supporting a data model (called BioStar) capturing the semantics of biomedical data and providing some extensibility to cope with the evolution of biological research methodologies.
BioStar models of clinical and genomic data for biomedical data warehouse design
International journal of bioinformatics research and applications
International journal of bioinformatics research and applications
Computer Science Medicine