Accelerating cancer systems biology research through Semantic Web technology. (27th November 2012)

• Record Type: Journal Article
• Authors: Wang, Zhihui; Sagotsky, Jonathan; Taylor, Thomas; Shironoshita, Patrick; Deisboeck, Thomas S.
• Is Part Of: Wiley interdisciplinary reviews. Volume 5:Number 2(2013)
• Page Start: 135
• Page End: 151
• Publication Date: 2012-11-27
• Subjects: Systems biology -- Periodicals; Medicine -- Periodicals; 610
• DOI: 10.1002/wsbm.1200
• Languages: English
• ISSNs: 1939-5094

Abstract

Abstract: Cancer systems biology is an interdisciplinary, rapidly expanding research field in which collaborations are a critical means to advance the field. Yet the prevalent database technologies often isolate data rather than making it easily accessible. The Semantic Web has the potential to help facilitate web‐based collaborative cancer research by presenting data in a manner that is self‐descriptive, human and machine readable, and easily sharable. We have created a semantically linked online Digital Model Repository (DMR) for storing, managing, executing, annotating, and sharing computational cancer models. Within the DMR, distributed, multidisciplinary, and inter‐organizational teams can collaborate on projects, without forfeiting intellectual property. This is achieved by the introduction of a new stakeholder to the collaboration workflow, the institutional licensing officer, part of the Technology Transfer Office. Furthermore, the DMR has achieved silver level compatibility with the National Cancer Institute's caBIG, so users can interact with the DMR not only through a web browser but also through a semantically annotated and secure web service. We also discuss the technology behind the DMR leveraging the Semantic Web, ontologies, and grid computing to provide secure inter‐institutional collaboration on cancer modeling projects, online grid‐based execution of shared models, and the collaboration workflow protecting researchers' intellectual property. WIREs Syst Biol Med 2013, 5:135–151. doi: 10.1002/wsbm.1200 This article is categorized under: Analytical and Computational Methods > Computational Methods Models of Systems Properties and Processes > Mechanistic Models