1. caBench-to- Bedside (caB2B) An easy to use tool for searching across caGrid Rakesh Nagarajan Washington University School of Medicine

2. Overview caB2B is a tool designed to integrate and analyze diverse biomedical datasets seamlessly. It has been developed to facilitate individual steps of cancer research analyses and reduce the bench-to-bedside barrier. caB2B is a caGrid client that permits bench scientists, translational researchers, and clinicians to leverage data services developed under caBIG® through a graphical user interface. Its metadata-based query interface enables end users to search virtually any caGrid data service.

3. Example Use Cases User can query for all pre-cancerous biospecimens from various caTissue instances like those at Washington University, Thomas Jefferson University, Holden Comprehensive Cancer Center etc. User can identify the sample obtained for Glioblastoma multiforme (GBM) and the corresponding CT image information. This query can be performed by querying across caTissue and NBIA using caB2B. User can find out if a sample used in an expression profiling experiment is available for a SNP analysis experiment. This query can be performed by querying across caTissue and caArray using caB2B. User can search for a particular gene based on the EntrezGeneID and its related information e.g. messenger RNA and protein information from GeneConnect.

4. caB2B Dependencies Availability of data on the caGrid Metadata registered in caDSR caGrid core services that support security, query federation and metadata Performance of the caGrid and data services

5. caB2B v3.1 Components caB2B Server Caches metadata (concept codes, class and attribute descriptions, and permissible values) from caDSR and service instances to query Persists query results and downstream analyses caB2B Administrative Module Permits caB2B server customization by the Administrator Allows for model metadata caching and service instance selection Permits Administrator to curate models (frequently used paths, creating categories, defining intermodel joins) in order to facilitate end user queries caB2B Client Application Allows end users to query virtually any caGrid data service, persist salient results, and examine this information using visualization windows caB2B Web Application Allows users to query microarray data, imaging data, and biospecimen data available on the caGrid. Permits keyword searches or use highly relevant parameterized queries (saved searches).

6. Target Audience caB2B Administrative Module Bioinformaticist -The caB2B administrator. Knowledge of UML models/domain models of caBIG tools is required; For activities like creating multi-model category, knowledge of Extensible Markup Language (XML) and basic knowledge of executing commands is desired. caB2B Client Application Clinical and Translational Research Scientist. Knowledge of UML models/domain models of caBIG tools is required to create and execute the queries using caB2B. caB2B Web Application Clinical and translational research scientist. No special knowledge or skill is required to use the caB2B web application.

7. Scenarios for caB2B Use Use GU/WashU/NCI instances to access public data available via production caGrid Use your institutional instance to access Public data available via production caGrid Private data available via institutional caGrid (local services) Use public/private instance to access Private data which only your (or your collaborator’s) caGrid credentials allow access to

8. caB2B Short Term Goals Improving usability and performance Addressing immediate researcher’s needs Reaching out to stakeholders for translational research use cases

9. caB2B Short Term Goals: Addressing researcher’s needs From Prostate SPOREs: Ability to search all biospecimens based on certain clinical and pathological annotations from caTissue Suite deployments at Prostate SPORE sites In response: UCLA will host their instance of caB2B. caB2B will support query of caTissue Core, Clinical Annotation, Pathology Annotation (for Specimen and Specimen Group) and Dynamic Extension Services.

10. caB2B Short Term Goals: Addressing researcher’s needs From Roswell Park: Conducting a pilot project to address larger initiative on issues with disparate databases and the difficulties gaining access to relevant clinical data for research. Grid enabling 4 different databases. Each database will have its own service with data elements mapped to caDSR. caB2B will be used to successfully query this data using CQL queries. The 4 databases are: Tumor Registry (SQL), Pathology System (SQL), Biobank/LIMS System (Oracle) and another biobanking system (MS Access). The group will expand upon this project and grid enable more databases if the pilot project is successful The group is interested in the caB2B Web Application for its ease of use for the clinicians and researchers. Ultimately, the group would like to give this tool to a central office that handles data and biospecimen requests. In response: caB2B team will support caB2B deployment at Roswell Park and help query across the resultant data services.

11. caB2B Longer Term Goals Continue to reach out to stakeholders for translational research use cases with the help from Knowledge Center Alignment to new Semantic Infrastructure, caGrid 2.0 and HL7 SAIF related activities Flexibility to support multiple platforms Tighter integration with related tooling supporting translational research E.g. caIntegrator, Georgetown Database of Cancer (G- DOC), Taverna, etc.

12. caB2B Longer Term Goals: Alignment to infrastructure activities With new Semantic Infrastructure, caGrid 2.0 and HL7 SAIF related activities, we might see: Various platforms Different metadata representation Different query capabilities …

13. caB2B Longer Term Goals: Flexibility to Support Multiple Platforms Query Language Response Data Format Metadata caBIG Query Language (CQL) XMLInformation Model (UML/XML/XMI) SPARQLRDFOntology (OWL) SQLCSV/XMLData Model (DDL/UML) XQueryXMLXML Schema (XSD) ……. For caGrid 1.x (supported)/2.x (?) For caGrid 2.x (?) Just some examples Goal is to provide the flexibility to support these by community contribution

14. caB2B Longer Term Goals: Integration with Other Tools

15. caB2B Development and Support caB2B Developers at Georgetown University www.georgetown.edu/ caB2B Knowledge Center at Washington University Medical School https://cabig-kc.nci.nih.gov/CaGrid/KC/index.php/CaB2B (Wiki Page)https://cabig-kc.nci.nih.gov/CaGrid/KC/index.php/CaB2B https://cabig-kc.nci.nih.gov/CaGrid/forums/ (Forums)https://cabig-kc.nci.nih.gov/CaGrid/forums/ Upcoming Webinars When: Tuesday, November 23, 2010; 3:00 PM-4:00PM EST Topic: caB2B Web Application Features. The KC will host a webinar to review and demonstrate feature of caB2B Web Application version 3.1 Registration: To register please visit https://www2.gotomeeting.com/register/472822523 https://www2.gotomeeting.com/register/472822523

16. 16 Useful Links caB2B Instances https://cab2b.nci.nih.gov/cab2b/ (National Cancer Institute)https://cab2b.nci.nih.gov/cab2b/ https://cab2b.wustl.edu/cab2b/ (Washington University School of Medicine)https://cab2b.wustl.edu/cab2b/ https://cab2b.georgetown.edu/cab2b (Georgetown University)https://cab2b.georgetown.edu/cab2b caB2B Tools Page https://cabig.nci.nih.gov/tools/caB2Bhttps://cabig.nci.nih.gov/tools/caB2B caB2B GForge https://gforge.nci.nih.gov/projects/cab2b/https://gforge.nci.nih.gov/projects/cab2b/

17. Acknowledgments Washington University Poornima Govindrao Mukesh Sharma Mark Watson Georgetown University Baris Suzek Jim Humphries Andrew Shinohara NCI-CBIIT Ian Fore Juli Klemm Avinash Shanbhag Anand Basu SAIC-Frederick, Inc. Rod Winkler Persistent Systems Srikanth Adiga Pooja Arora Gaurav Mehta Pallavi Mistry Chetan Patil Chetan Pundhir Deepak Shingan Madhumita Shrikhande Chandrakant Talele Rajesh Vyas Capability Plus Solutions Chris Piepenbring Sapient Stephen Goldstein 17