Showing papers presented at "Semantic Web Applications and Tools for Life Sciences in 2009"
Proceedings Article•
01 Jan 2009TL;DR: A text mining approach that utilises the literature to automatically extract descriptions and semantically profile bioinformatics resources to make them available for resource discovery and exploration through semantic networks that contain related resources demonstrates the potential of combining literature mining and simple lexical kernel methods to model relatedness between resource descriptors in particular when there are few features.
Abstract: There have been a number of recent efforts (e.g. BioCatalogue, BioMOBY, etc.) to systematically catalogue bioinformatics tools, services and datasets. These efforts mostly rely on manual curation and are unable to cope with the huge influx of various electronic resources, which consequently result in their unavailability to the community. We present a text mining approach that utilizes the literature to extract and semantically profile bioinformatics resources. Our method identifies the mentions of resources in the literature and assigns a set of co-occurring terminological and ontological entities (descriptors) to represent them. Since such representations can be extremely sparse, we use kernel metrics based on lexical term/descriptor similarities to identify semantically related resources. Resources are then either clustered or linked into a network, providing the users (bioinformaticians and service/tool crawlers) with a possibility to explore tools, services and datasets based on their relatedness, thus potentially improving the resource discovery process.
9 citations
Proceedings Article•
01 Dec 2009
TL;DR: This work has developed a methodology for translating OBO ontologies to OWL using the organization of the Semantic Web layer cake to guide the work, and developed a standard common mapping between OBO and OWL for the OBO community.
6 citations
Proceedings Article•
01 Jan 2009TL;DR: Developing ontologies is not an easy task and often the resulting ontologies are not consistent or strucurally complete, so such ontologies also lead to problems when used in practice.
Abstract: Developing ontologies is not an easy task and often the resulting ontologies are not consistent or strucurally complete. Such ontologies, although often useful, also lead to problems when used in s ...
4 citations
Proceedings Article•
01 Jan 2009TL;DR: An ontology-based system that helps users manage knowledge using Wikipedia and uses the structural information about the ontologies to re-structure contents of Wikipedia for better browsing is presented.
Abstract: In this paper, we present an ontology-based system that helps users manage knowledge using Wikipedia. The system analyzes ontologies and uses the structural information about the ontologies to re-structure contents of Wikipedia for better browsing. Using the system, users can acquire knowledge easily from Wikipedia. We show how the system can be used for life science applications.
2 citations
Proceedings Article•
01 Jan 2009TL;DR: This work has shown that the Ondex data integration platform, which enables data from diverse biological data sets to be linked together, integrated, analysed and visualised using graph-based techniques, supports a limited representation of ontologies.
Abstract: The Ondex data integration platform [1] (www.ondex.org) enables data from diverse biological data sets to be linked together, integrated, analysed and visualised using graph-based techniques. At the basis of Ondex is a graph data structure where entities and properties are associated to classes [2]. This data structure is closely related to the data model of RDF and supports a limited representation of ontologies.