A relational model of data for large shared data banks
Communications of the ACM
DiscoveryLink: a system for integrated access to life sciences data sources
IBM Systems Journal - Deep computing for the life sciences
Putting Semantics into e-Science and Grids
E-SCIENCE '05 Proceedings of the First International Conference on e-Science and Grid Computing
Semantic Web Service provision
Bioinformatics
R Programming for Bioinformatics
R Programming for Bioinformatics
Metadata-driven software for clinical trials
SEHC '09 Proceedings of the 2009 ICSE Workshop on Software Engineering in Health Care
Managing Chaos: Lessons Learned Developing Software in the Life Sciences
IEEE Design & Test
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This paper discusses a general purpose software architecture, called Addama, which is used to support the rapid integration and analysis of high volumes of complex biological data. It does this by providing: adaptable software which enables interoperable data access; a step-wise and flexible integration strategy, allowing new information to be overlaid on top of existing annotations and context graphs; and through the provision of asynchronous messaging to support rapid integration of new analysis mechanisms. This work is illustrated through the Cancer Genome Atlas (TCGA) study. Addama is being used within a TCGA analysis center to identity new therapeutic intervention approaches by equating clinical outcomes with underlying genomic effects across heterogeneous data from approximately 20,000 patient samples. Addama supports projects like the TCGA through accepting that biological understanding continually changes, and that the rapid integration of new information and analyses is an essential requirement when supporting research.