The semantic web in translational medicine: current applications and future directions

Abstract

Semantic web technologies offer an approach to data integration and sharing, even for resources developed independently or broadly distributed across the web. This approach is particularly suitable for scientific domains that profit from large amounts of data that reside in the public domain and that have to be exploited in combination. Translational medicine is such a domain, which in addition has to integrate private data from the clinical domain with proprietary data from the pharmaceutical domain. In this survey, we present the results of our analysis of translational medicine solutions that follow a semantic web approach. We assessed these solutions in terms of their target medical use case; the resources covered to achieve their objectives; and their use of existing semantic web resources for the purposes of data sharing, data interoperability and knowledge discovery. The semantic web technologies seem to fulfill their role in facilitating the integration and exploration of data from disparate sources, but it is also clear that simply using them is not enough. It is fundamental to reuse resources, to define mappings between resources, to share data and knowledge. All these aspects allow the instantiation of translational medicine at the semantic web-scale, thus resulting in a network of solutions that can share resources for a faster transfer of new scientific results into the clinical practice. The envisioned network of translational medicine solutions is on its way, but it still requires resolving the challenges of sharing protected data and of integrating semantic-driven technologies into the clinical practice.

BiOSS: A system for biomedical ontology selection

“…As a consequence, in the biomedical field it is becoming increasingly important to develop automatic methods and tools to select the best ontologies to describe particular datasets or to be used as the basis of specific applications (e.g. [37][38][39][40][41][42][43]).…”

Biomedical Semantic Resources for Drug Discovery Platforms

“…GenBank 17 is an open-access annotated collection of all publicly available nucleotide sequences and their protein translations. GenBank and its collaborators receive sequences produced in laboratories throughout the world from more than 380'000 distinct organisms.…”

“…The semantic connectivity between biomedical data constitutes a critical issue of biomedical scientific research and has been successfully exploited in a number of research projects for transitional medicine and drug discovery [17]. Moreover the adoption of linked data technologies will allow the integration of biomedical datasets provided by different and heterogeneous data sources (i.e.…”

DINTO: Using OWL Ontologies and SWRL Rules to Infer Drug–Drug Interactions and Their Mechanisms

“…Semantic web technologies, and specifically ontological engineering, can provide the techniques and tools necessary to overcome these issues. 29 The semantic web has been postulated as the solution for data integration over disparate biomedical domains, 30 supported by standards such as OWL 31 and its extension SWRL. 32 −34 In this framework, we propose the creation of a comprehensive ontology for drug−drug interactions knowledge, DINTO, a resource designed to be used by the computational community working on applications within the DDI domain.…”