repositories, where each of the objects is annotated with controlled vocabulary (CV) terms from two ontologies. Using a set of LSLink instances generated from a background dataset of knowledge we identify associations between pairs of CV terms that are potentially significant and may lead to new knowledge. We

-free transcription assays showed that Pol III, but not Pol II, is associated with miRNA genomic sequence and sufficient for transcription. Moreover, the mature miRNA sequences of approximately 50 additional human miRNAs lie within Alu and other known repetitive elements. These findings extend the current view of mi

Initiative, and called OLAC – the Open Language Archives Community. The OLAC Metadata Set and the associated controlled vocabularies facilitate consistent description and focussed searching. We report progress on the metadata set and controlled vocabularies, describing current issues and soliciting input

Annotation graph datasets are a natural representation of scientific knowledge. They are common in the life sciences and health sciences, where concepts such as genes, proteins or clinical trials are annotated with controlled vocabulary terms from ontologies. We present a tool, PAnG (Patterns

on the Open Archives Initiative, and called OLAC -- the Open Language Archives Community. The OLAC Metadata Set and the associated controlled vocabularies facilitate consistent description and focussed searching. We report progress on the metadata set and controlled vocabularies, describing current

Abstract. Annotation graph datasets are a natural representation of scientific knowledge. They are common in the life sciences where con-cepts such as genes and proteins are annotated with controlled vocabu-lary terms from ontologies. Scientists are interested in analyzing or min

There is an increasing need to automatically annotate a set of genes or proteins (from genome sequencing, DNA microarray analysis or protein 2D gel experi-ments) using controlled vocabularies and identify the pathways involved, especially the statistically enriched pathways. We have previously

Abstract. Linked Open Data initiatives have made available a diversity of collections that domain experts have annotated with controlled vocabulary terms from ontologies. The challenge is to explore these rich and complex annotated datasets, together with the domain semantics captured within

Abstract. Annotation graph datasets are a natural representation of scientific knowledge. They are common in the life sciences where genes or proteins are annotated with controlled vocabulary terms (CV terms) from ontologies. The W3C Linking Open Data (LOD) initiative and semantic Web technologies

High-quality annotation of biological data is central to bioinformatics. Annotation using terms from ontologies provides reliable computational access to data. The Gene Ontology (GO), a structured controlled vocabulary of nearly 17,000 terms, is becoming the de facto standard for describing