ArticleInternational journal of bioinformatics research and applications2005
BioStar models of clinical and genomic data for biomedical data warehouse design.
Article in International journal of bioinformatics research and applications, 2005. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
4 citing papers in PubMed.
- Processing genome-wide association studies within a repository of heterogeneous genomic datasets.BMC genomic data · 2023Article
- Methodological Guidelines for Reducing the Complexity of Data Warehouse Development for Transactional Blood Bank Systems.Decision support systems · 2013Article
- BEAT: Bioinformatics Exon Array Tool to store, analyze and visualize Affymetrix GeneChip Human Exon Array data from disease experiments.BMC bioinformatics · 2012Article
- BioGPS: an extensible and customizable portal for querying and organizing gene annotation resources.Genome biology · 2009Article
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Authors and funding
3 authors.
Funding
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.
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Registered trials
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