Olivier Bodenreider
National Library of Medicine
USA

Terminological systems in biomedicine: From terminology integration to information integration.

The use of different names and codes for the same entity in different terminologies has long been identified as a barrier to integrating biomedical information sources. By integrating terms from many disparate biomedical sources, terminological systems help bridge across terminologies. And because terms and codes constitute an entry point into information sources, terminology integration represents a key element to information integration.
As an example of terminological system, we briefly introduce the Unified Medical Language System (UMLS), a resource integrating more than one hundred biomedical terminologies. We show how integrative resources such as the UMLS can play a role to bridge across namespaces in the Semantic Web.
Translational research requires the integration of information between the "bench" (basic research) and the "bedside" (clinical practice).
Using the example of oncology, we show practical issues in the integration of cancer terminologies.

Olivier Bodenreider is a Staff Scientist in the Cognitive Science Branch of the Lister Hill National Center for Biomedical Communications at the U.S. National Library of Medicine. His research interests include terminology, knowledge representation and ontology in the biomedical domain, both from a theoretical perspective and in their application to natural language understanding, reasoning, information visualization and integration. Dr. Bodenreider is a Fellow of the American College of Medical Informatics. He received a M.D. degree from the University of Strasbourg, France in 1990 and a Ph.D. in Medical Informatics from the University of Nancy, France in 1993. Before joining NLM in 1996, he was an assistant professor for Biostatistics and Medical Informatics at the University of Nancy, France, Medical School.

Sophia Ananiadou
University of Manchester
UK

Delivering Text Mining Services for the Biosciences

The UK National Centre for Text Mining is providing text mining services for the Biosciences. These services range from terminology management, to advanced information retrieval, semantic querying, relation mining and are customised for different users. NaCTeM provides users with a coherent interoperable set of core text mining tools through adoption of UIMA. The Centre is also building bio-resources and annotated corpora.
Last, NaCTeM’s current and future benefits to the UK research community and its future vision will be presented.

Sophia Ananiadou is Reader in Text Mining in the School of Computer Science at the University of Manchester and Deputy Director of the National Centre for Text Mining (NaCTeM). She is the main developer of the terminology management services provided by NaCTeM. Her current research includes building bio-resources, advanced IR systems, the text-mining-based visualisation of the provenance of biochemical networks and text mining for systematic reviews. She is recipient of the 2004 Daiwa Adrian prize for her research in Knowledge Mining for Biology, and in 2006 of the IBM UIMA innovation award for her work on the interoperability of text-mining tools.

Patrick Lambrix
Linköpings Universitet
Sweden

Aligning biomedical ontologies

The use of ontologies is a key technology for the Semantic Web and in particular in the biomedical field many ontologies have already been developed. Many of these ontologies, however, contain overlapping information and to make full use of the advantages of ontologies it is important to know the inter-ontology relationships, i.e. we need to align the ontologies. Knowledge of these alignments would lead to improvements in search, integration and analysis of biomedical data. It has been realized that this is a major issue and some organizations have started to deal with it.
In this talk we give an overview of techniques for ontology alignment with a focus on approaches that compute similarity values between terms in the different ontologies. Further, we discuss the results of evaluations of these techniques using biomedical ontologies. Finally, we discuss the recent development of approaches for providing recommendations of ontology alignment strategies for a given alignment task.

Patrick Lambrix is a professor of bioinformatics/knowledge engineering at Linköpings universitet, Sweden. His current research interests relate to the areas of semantic web, ontologies, databases and bioinformatics and he leads projects on alignment of biomedical ontologies and grouping of biological data. He received MSc degrees in mathematics (1988) and computer science (1990) from KU Leuven, Belgium and a PhD degree in computer science from Linköpings universitet (1996).