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The Gene Regulation Ontology (GRO) is designed as a novel approach to model complex events that are part of the gene regulatory processes. We introduce the design requirements for such a conceptual model and discuss terminological resources suitable to base its construction on. The ontology defines gene regulation events in terms of ontological classes and(More)
MOTIVATION Gene Ontology (GO) has been manually developed to provide a controlled vocabulary for gene product attributes. It continues to evolve with new concepts that are compiled mostly from existing concepts in a compositional way. If we consider the relatively slow growth rate of GO in the face of the fast accumulation of the biological data, it is much(More)
As the importance of automatically extracting and analyzing various natural language assertions about protein-protein interactions in biomedical publications is recognized, many uses of natural language processing techniques are proposed in the literature. However, most proposals to date make rather simplifying assumptions about the syntactic aspects of(More)
UNLABELLED Search engines running on MEDLINE abstracts have been widely used by biologists to find publications that are related to their research. The existing search engines such as PubMed, however, have limitations when applied for the task of seeking textual evidence of relations between given concepts. The limitations are mainly due to the problem that(More)
Biomedical researchers have to efficiently explore the scientific literature, keeping the focus on their research. This goal can only be achieved if the available means for accessing the literature meet the researchers' retrieval needs and if they understand how the tools filter the perpetually increasing number of documents. We have examined existing(More)
UNLABELLED Gene ontology (GO) annotation is a common task among model organism databases (MODs) for capturing gene function data from journal articles. It is a time-consuming and labor-intensive task, and is thus often considered as one of the bottlenecks in literature curation. There is a growing need for semiautomated or fully automated GO curation(More)
MOTIVATION Contrasts are useful conceptual vehicles for learning processes and exploratory research of the unknown. For example, contrastive information between proteins can reveal what similarities, divergences and relations there are of the two proteins, leading to invaluable insights for better understanding about the proteins. Such contrastive(More)
BACKGROUND The extraction of complex events from biomedical text is a challenging task and requires in-depth semantic analysis. Previous approaches associate lexical and syntactic resources with ontologies for the semantic analysis, but fall short in testing the benefits from the use of domain knowledge. RESULTS We developed a system that deduces implicit(More)