Collaborative Technology Projects

One of the key guiding principles of the CVRG is that we don’t “re-invent the wheel”. We re-use and extend software from other grid projects whenever possible, focusing on development of CV-specific resources. To do this, we have formed Collaborating Technology Projects (CTPs) focused on joint, mutually beneficial technology development with the CVRG team. There are currently six CTPs. The rapid addition of new CTPs demonstrates that we are well integrated into the technology development community, and that we are leveraging these collaborations so that technology development extends far beyond the initial CVRG team.

BIRN:

The CVRG is working with the Biomedical Informatics Research Network on aspects of medicine that overlap between cardiovascular research and neuroscience. These areas include computational anatomy, electrophysiological ontology development, and DICOM image data management.

caBIG/caGrid:

The CVRG is working with the cancer Biomedical Informatics Grid on aspects of technology that deal with systems biology and clinical research data sharing and integration.

caGrid XML Data Service:

The caGrid XML Data Service Framework is an extension of caGrid for querying and retrieving XML documents managed in XML databases. XML Data Service provides extension to Introduce for flexible and rapid creation of caGrid Data Services from existing XML schemas. It is a caGrid Community Project.

Cardiac Atlas Project:

The Cardiac Atlas Project is developing atlases of the heart for a number of application in biophysical analysis of cardiac electromechanics. A collaboration project (PAR-07-426 and NOT-HL-08-103) with the CVRG is in review.

Data Ontologies for Integrating Cardiovascular Epidemiological Studies (D.C. Rao, T. Rice, R. Nagarajan):

Cardiovascular disease (CVD) risk factors such as hypertension and dyslipidemia are common complex traits that constitute a major public-health burden due to increased mortality, morbidity and health care costs. These phenotypes are considered complex traits precisely because they entail multiple genetic and environmental causes, each with a small effect, that act together to produce the disease trait. For these reasons, massive epidemiological study data are needed to detect these small individual effects and their interactions. However, due to sample size limitations of any given study, only integration of multiple epidemiological studies can yield the type of sample sizes needed to make powerful inferences. Moreover, CVD itself is measured across a myriad of dimensions, and not all dimensions are evaluated in each of the many studies. Therefore, the scientist must be able to integrate and analyze data from often disparate studies. However, meaningful integration of information from multiple studies requires the development of data ontologies which make it possible to integrate information across studies in an optimum manner so as to maximize the information content and hence the statistical power for detecting the small effect sizes. Consequently, there is a growing need to streamline the management and accessibility of large disparate databases using common bioinformatic tools that are amenable to the evolving nature of research, that can integrate across study-specific information into common data elements, and do all this in a way that is informative and user-friendly from the end user’s point of view. Accordingly, this proposal is devoted to the development of ontologies for integrating cardiovascular epidemiological data from multiple studies.

Grid of Grids:

The CVRG is working with the caBIG Knowledge Center to provide coordinated service security and indexing between the CVRG and caBIG.

National Center for Biomedical Ontologies Driving Biomedical Project:

CVRG is working with the NCBO to develop tools for manual and automated annotation of biomedical time-series data. (see NCBO DBP).