Exploitation of ontological resources for scientific literature analysis: searching genes and related diseases.

Ontological resources such as controlled vocabularies, taxonomies and ontologies from the OBO foundry are used to represent biomedical domain knowledge. The development of such resources is a time consuming task. Once they are finished they contribute to standardization of information representation, interoperability of IT solutions, literature analysis and knowledge discovery. Text mining comprises IT solutions for information retrieval (IR) and information extraction (IE). IR technology exploits ontological resources to select documents that fit best to the processed query, for example, through indexing of the literature content with concept ids or through disambiguation of terms in the query. IE solutions make use of the ontological labels to identify concepts in the text. The text passages that denote conceptual entries are then used either to annotate named entities or to relate the named entities to each other. For knowledge discovery (KD) solutions the identified concepts in the scientific literature are used to relate entities to each other, e.g. to identify gene-disease relations based on shared molecular functions.

Reuse of terminological resources for efficient ontological engineering in Life Sciences.

This paper is intended to explore how to use terminological resources for ontology engineering. Nowadays there are several biomedical ontologies describing overlapping domains, but there is not a clear correspondence between the concepts that are supposed to be equivalent or just similar. These resources are quite precious but their integration and further development are expensive. Terminologies may support the ontological development in several stages of the lifecycle of the ontology; e.g. ontology integration. In this paper we investigate the use of terminological resources during the ontology lifecycle. We claim that the proper creation and use of a shared thesaurus is a cornerstone for the successful application of the Semantic Web technology within life sciences. Moreover, we have applied our approach to a real scenario, the Health-e-Child (HeC) project, and we have evaluated the impact of filtering and re-organizing several resources. As a result, we have created a reference thesaurus for this project, named HeCTh.

XML-based approaches for the integration of heterogeneous bio-molecular data.

BACKGROUND: The today's public database infrastructure spans a very large collection of heterogeneous biological data, opening new opportunities for molecular biology, bio-medical and bioinformatics research, but raising also new problems for their integration and computational processing. RESULTS: In this paper we survey the most interesting and novel approaches for the representation, integration and management of different kinds of biological data by exploiting XML and the related recommendations and approaches. Moreover, we present new and interesting cutting edge approaches for the appropriate management of heterogeneous biological data represented through XML. CONCLUSION: XML has succeeded in the integration of heterogeneous biomolecular information, and has established itself as the syntactic glue for biological data sources. Nevertheless, a large variety of XML-based data formats have been proposed, thus resulting in a difficult effective integration of bioinformatics data schemes. The adoption of a few semantic-rich standard formats is urgent to achieve a seamless integration of the current biological resources.