Data Set Used
MOTIVATION Integrative mathematical and statistical models of cardiac anatomy and physiology can play a vital role in understanding cardiac disease phenotype and planning therapeutic strategies. However, the accuracy and predictive power of such models is dependent upon the breadth and depth of noninvasive imaging datasets. The Cardiac Atlas Project (CAP)… (More)
MOTIVATION Ontology development and the annotation of biological data using ontologies are time-consuming exercises that currently require input from expert curators. Open, collaborative platforms for biological data annotation enable the wider scientific community to become involved in developing and maintaining such resources. However, this openness… (More)
Large knowledge bases integrating different domains can provide a foundation for new applications in biology such as data mining or automated reasoning. The traditional approach to the construction of such knowledge bases is manual and therefore extremely time consuming. The ubiquity of the internet now makes large-scale community collaboration for the… (More)
As the amount of data being generated in biology has increased , a major challenge has been how to store and represent this data in a way that makes it easily accessible to researchers from diverse domains. Understanding the relationship between genotype and phenotype is a major focus of biological research. Various approaches to providing the link between… (More)
Objective To develop a statistical map of regional wall motion in healthy and diseased populations using a standardized database of cardiovascular magnetic resonance studies.
The Cardiac Atlas Project (CAP) is a NIH sponsored international collaboration to establish a web-accessible structural and functional atlas of the normal and pathological heart as a resource for the clinical, research and educational communities. An initial goal of the atlas is to facilitate statistical analysis of regional heart shape and wall motion… (More)