CVRG ECG Physionet Data Service CVRG Institute for Computational Medicine Stephen Granite PhysioNet was established in 1999 as the outreach component of the Research Resource for Complex Physiologic Signals. Its PhysioBank is a large and growing archive of well-characterized digital recordings of physiologic signals and related data for use by the biomedical research community. The Physionet data service leverages the XML Data Service, developed jointly by the caBIG In Vivo Imaging workspace and the CVRG. Through the XML Data Service, metadata about the WFDB files are stored in an open-source embeddable Oracle Berkeley DB XML database. The WFDB files themselves are stored in a referenced location on the CVRG file system. ECG Physionet "Data Service" David Hopkins Johns Hopkins University (410) 516-8849 sgranite@jhu.edu http://cvrgrid.org/?q=content/cvrg-data-services CVRG GWT Gadgets "Google Web Toolkit Dashboard" "Gadget" "ECG" "Federated Query" "Decision Tree" (410) 516-8849 Johns Hopkins University Stephen Granite http://cvrgrid.org/?q=node/113 CVRG David Hopkins Institute for Computational Medicine The CVRG team has developed a dashboard interface by which users login to access CVRG resources. The Dashboard is built using Web 2.0 technologies (the Google Web Toolkit – GWT; and Visualization API - GVAPI), is lightweight, “load-and-go”, and provides a secure authentication and authorization mechanism. sgranite@jhu.edu http://cvrgrid.org/?q=CVRG_Analytical_Services CVRG Multi-Scale Biomarker Discovery David Hopkins CVRG Multi-Scale Biomarker Discovery Johns Hopkins University sgranite@jhu.edu Stephen Granite Institute for Computational Medicine (410) 516-8849 Translational CV research more often than not involves the collection and analysis of what we refer to as multi-scale data sets (SNP, mRNA expression, protein expression, imaging, ECG, clinical, etc) for each patient in large cohorts. A challenge is to analyze such multi-scale data sets to discover biomarkers that are predictive of disease risk and treatment. Algorithms for biomarker discovery are available through the Biomarker discovery portlet. Algorithms include the K-TSP family of classifiers, known to be useful when the number of analysis features is large relative to the number of datasets. [See Geman D, d'Avignon C, Naiman DQ, Winslow RL. (2004) Classifying gene expression profiles from pairwise mRNA comparisons. Stat. Appl. Genet. Mol. Biol., 3(1): Article 19 and Xu L, Geman D, Winslow RL. (2007) Large-scale integration of cancer microarray data identifies a robust common cancer signature. BMC Bioinformatics. 8:275.]. http://cvrgrid.org/?q=CVRG_Analytical_Services Heart Shape and Motion Analysis Services David Hopkins CVRG The Large Deformation Diffeomorphic Metric Mapping (LDDMM) algorithm is the most widely used algorithm for analyzing anatomic shape and it’s variation [see Beg, M.F., Miller, M.I., Trouve, A., Younes, L. (2005). Computing Large Deformation Metric Mappings via Geodesic Flows of Diffeomorphisms. International Journal of Computer Vision 61, 139-157.]. It has been used extensively in brain research to discover shape-based biomarkers that are signatures of brain disease. We have recently used the LDDMM algorithm to study shape changes, assessed using MR and CT imagery collected from ex-vivo and in-vivo hearts, that are signatures of heart disease collected from ex-vivo and in-vivo hearts. [See Beg, M. F., Helm, P. A., McVeigh, E., Miller, M. I. and Winslow, R. L. (2004). Computational Cardiac Anatomy Using MRI. Magn. Reson. Med., 52(5): 1167 and Helm, P. et al (2006). Circ. Res. 98(1): 125-132]. Users may access the LDDMM algorithm using MRI Studio. MRI Studio is a Windows application that supports image volume visualization, diffusion tensor calculations, fiber tracking and editing, region of interest selection, and diffeomorphic mapping using the LDDMM algorithm. Computations may be performed using CVRG compute resources. Interested users should contact the CVRG team at cvrgbeta@gmail.com. Stephen Granite (410) 516-8849 sgranite@jhu.edu Johns Hopkins University Institute for Computational Medicine CVRG Heart Shape and Motion Analysis Services (410) 516-8849 http://cvrgrid.org/?q=content/cvrg-data-services David Hopkins Protein DB Version 2.0 is a full-featured proteomics data service based on the PSI-OM. Protein DB has been harmonized with the caBIG caDSR and can be viewed in the NCI UML Model Browser. A data model is available on the JHU Proteomics Center site. Institute for Computational Medicine Stephen Granite sgranite@jhu.edu CVRG Protein DB "Data Service" Johns Hopkins University CVRG Protein DB Data Service David Hopkins Johns Hopkins University CVRG The DICOM image data service (DICOMDataService) has been instantiated at JHU. It leverages an Open-Source Clinical Image Management system (DCM4CHE). Access to the system is currently available through the use of virtualPACS and instructions for installing virtualPACS are available in the CVRG Wiki site sgranite@jhu.edu CVRG DICOM Image Data Service DICOM Image "Data Service" Institute for Computational Medicine Stephen Granite http://cvrgrid.org/?q=content/cvrg-data-services (410) 516-8849 (410) 516-8849 The Cardiovascular Research Grid David Hopkins Stephen Granite Johns Hopkins University Institute for Computational Medicine CVRG The aim of the CardioVascular Research Grid (CVRG) project is to create an infrastructure for sharing cardiovascular data and data analysis tools. The CVRG will support national and international multi-institutional collaborations in cardiovascular science, and will build on and extend tools developed in the caBIG and BIRN projects. The CVRG project is supported by the National Heart Lung & Blood Institute. The project is based at the Institute for Computational Medicine at Johns Hopkins University, in collaboration with the Center for Comprehensive Informatics at Emory University. http://www.cvrgrid.org sgranite@jhu.edu CVRG David Hopkins OpenClinica "Data Service" http://cvrgrid.org/?q=content/cvrg-data-services Institute for Computational Medicine Johns Hopkins University sgranite@jhu.edu The OpenClinica Data Service provides grid-enabled access to clinical data. The service uses a PostgreSQL version 8.1.11 database and a data model developed in caCORE 4.0. More information about the data service is available on the CVRG Wiki site. (410) 516-8849 CVRG OpenClinica Data Service Stephen Granite Stephen Granite (410) 516-8849 http://cvrgrid.org/?q=content/cvrg-data-services David Hopkins Johns Hopkins University Institute for Computational Medicine CVRG In 2004, the Food & Drug Administration announced its intent to accept annotated ECG waveform data in XML following the Health Level 7 (HL7) Annotated ECG Waveform Data Standard (aECG). The HL7aECG data service leverages the XML Data Service, developed jointly by the caBIG In Vivo Imaging workspace and the CVRG. The HL7aECG files are stored within in an open-source embeddable Oracle Berkeley DB XML database. More information about the data service is available on the CVRG Wiki site CVRG ECG HL7aECG Data Service sgranite@jhu.edu ECG HL7aECG "Data Service" Institute for Computational Medicine David Hopkins The CVRG Portal provides an interface by which users may upload and analyze ECG data. This is known as the ECG Portlet. Two data formats are currently accepted. The first is the proprietary data format (RDT) used by Norav Instruments Inc. The second is the WaveForm DataBase (WFDB) format used in the Physionet Project. Files may be uploaded individually or in batches. Two ECG data analysis algorithms are available. The first is a suite of algorithms developed by Dr. Ron Berger at Johns Hopkins University. [See Berger, R.D., Kasper, E.K., Baughman K.L., Marban E., Calkins H., Tomaselli G.F. (1997) Beat-to-beat QT interval variability: novel evidence for repolarization lability in ischemic and nonischemic dilated cardiomyopathy. Circulation. 96(5):1557-1565 and Berger, R.D. (2003). QT Variability. J. Electrocardiol. 36: 83-87]. The second is a semi-automated algorithm developed as part of the Physionet competition by Chesnokov et al, which is described at the Physionet website. Data may be passed into these algorithms, the results are retrieved by the portlet, a subset of analysis results is displayed, and users may download all numeric results and import them into an Excel spreadsheet. Johns Hopkins University Stephen Granite http://cvrgrid.org/?q=CVRG_Analytical_Services CVRG ECG Data Analysis Service Yes ECG Data Analysis Service (410) 516-8849 sgranite@jhu.edu CVRG SNP "Data Service" David Hopkins sgranite@jhu.edu The SNP Data Service provides grid-enabled access to SNP data. The service uses a MySQL version 5.0.22 database and a data model developed in caCORE 3.2.1. (410) 516-8849 Johns Hopkins University CVRG CVRG SNP Data Service http://cvrgrid.org/?q=content/cvrg-data-services Institute for Computational Medicine Stephen Granite