Semantic Web meets Integrative Biology: a survey

B RIEFINGS IN BIOINF ORMATICS . VOL 14. NO 1. 109^125 Advance Access published on 6 April 2012 doi:10.1093/bib/bbs014 Semantic Web meets Integrative Biology: a survey Huajun Chen, Tong Yu and JakeY. Chen Submitted: 27th December 2011; Received (in revised form) : 18th February 2012 Abstract Keywords: semantic web; integrative biology; web ontology; web of data INTRODUCTION Integrative Biology (IB) lies at the intersection of a multitude of scientific and technological disciplines, and focuses on bridging the gap between different disciplines and the wedding of technological advances to biological insight. In the 1980s it was recognized that biology bounded by traditional disciplines no longer reflected the best way to do science, which created new Corresponding author. Huajun Chen, College of Computer Science, Zhejiang University, Hangzhou, 310027, P.R. China. Tel: 86-571-87953703; Fax: 86-571-87953079; E-mail: ; Tong Yu, College of Computer Science, Zhejiang University, Hangzhou, 310027, P.R. China. Tel: 86-571-87953703; Fax: 86-571-87953079; E-mail: ; Jake Y. Chen, Walker Plaza Building (WK), Suite #190, 719 N. Indiana Ave Indianapolis, IN 46202, USA (317) 2787604. E-mail: Huajun Chen is an associate professor of college of computer science, Zhejiang University. His major research interests include the Semantic Web, Ontologies, Biomedical Informatics and Traditional Chinese Medicine Informatics. He is particularly active in researches on the applications of the Semantic Web technologies in Life Sciences and Healthcares. He was the chair or co-chair of WWW2007/WW2008’s workshop on Semantic Web for Health Care and Life Science. He was the guest editors for several relevant special issues including BMC Bioinformatics special issue on ‘Semantic e-Science for Biomedicine’ (2007), Journal of Biomedical Informatics special issue on ‘Semantic BioMed Mashup’ (2008), CurrentBioinformatics special issue on ‘Semantic Web meets Current Bioinformatics’ (2012). He was an invited expert of W3C’s HCLS IG group. He is the executive member of the council of the Information Committee of World Federation of Chinese Medicine Societies. Tong Yu is a PhD candidate of Zhejiang University. His major interests include the Semantic Web, bioinformatics and integrative biomedicine. Jake Y. Chen is an associate professor of Informatics and Computer Science, Indiana University School of Informatics and Purdue University, Department of Computer & Information Science. He is the founding director of Indiana Center for Systems Biology and Personalized Medicine, and the advisory committee members of IU School of Medicine Translational Genomics Core IU Center for Environmental Health. He is the chair of Engineering in Medicine & Biology Society, IEEE Central Indiana Section (since 2005), steering committee and co-founder of Indiana Biomedical Entrepreneur Network (since 2004), systems biology chair and proteomics chair of the Life Sciences Society (since 2005), also serves as board member and vice president of association of Chinese bioinformaticians, (since 2001). His primary research areas: Translational Bioinformatics, Computational Systems Biology, Scientific Data Management and Data Mining, Semantic Web and Ontologies. ß The Author 2012. Published by Oxford University Press. For Permissions, please email: Integrative Biology (IB) uses experimental or computational quantitative technologies to characterize biological systems at the molecular, cellular, tissue and population levels. IB typically involves the integration of the data, knowledge and capabilities across disciplinary boundaries in order to solve complex problems. We identify a series of bioinformatics problems posed by interdisciplinary integration: (i) data integration that interconnects structured data across related biomedical domains; (ii) ontology integration that brings jargons, terminologies and taxonomies from various disciplines into a unified network of ontologies; (iii) knowledge integration that integrates disparate knowledge elements from multiple sources; (iv) service integration that build applications out of services provided by different vendors. We argue that IB can benefit significantly from the integration solutions enabled by Semantic Web (SW) technologies.The SW enables scientists to share content beyond the boundaries of applications and websites, resulting into a web of data that is meaningful and understandable to any computers. In this review, we provide insight into how SW technologies can be used to build open, standardized and interoperable solutions for interdisciplinary integration on a global basis. We present a rich set of case studies in system biology, integrative neuroscience, bio-pharmaceutics and translational medicine, to highlight the technical features and benefits of SW applications in IB. 110 Chen et al. solution, which is crucial to support the interdisciplinary integration. The first truly global integration solution is the World Wide Web. In 1990, Tim Berners-Lee invented the Web, in support of the cross-boundary information sharing and collaborative research in CERN [9]. Since its inception, the World Wide Web has changed the ways scientists communicate, collaborate and educate [10]. The Web enables the development and maintenance of cyber infrastructure for e-Science, which facilitates data sharing and interdisciplinary collaborations on a global basis [11]. However, the current Web still lacks a widelyaccepted and standard way to publish and share structured data, leading to the difficulty of achieving global data integration [12]. In order to fill the data gap on the Web, Tim Berners-Lee et al. envisioned the Semantic Web (SW) as a web of data that is meaningful and understandable to any computers [13, 14]. As they have predicted, the Web of data will enable Web users to share structured data as easy as they share documents, photos and videos today. As shown in Figure 1, the Web of data can be conceptualized as a global graph of things, or the graph layer on top of the Web [15]. Intelligent agents can operate directly on the Web of data in order to solve complex problems and accomplish intelligent tasks. This new layer leads to the emergence of Web 3.0 applications, which use the Web of data to augment the underlying Web system’s functionalities such as information retrieval and knowledge sharing [16]. Technically speaking, the SW is closely associated with the notion of ‘ontology’, which refers a computational model that can be used to explicitly represent the meaning of terms and the relationships between those terms [17–19]. The SW can support the collaborative engineering of domain ontologies that are shared by a community, and the use of ontologies to describe Web resources including knowledge, data and services. This approach not only enables digital resources to be shared and interconnected beyond the boundaries of applications and websites, but also supports the impl (...truncated)