Data Integration in the Life Sciences

DILS 2004 (Data Integration in the Life Sciences) is a new bioinformatics wo- shop focusing on topics related to data management and integration. It was motivated by the observation that new advances in life sciences, e. g. , molecular biology, biodiversity, drug discovery and medical research, increasingly depend on bioinformatics methods to manage and analyze vast amounts of highly - verse data. Relevant data is typically distributed across many data sources on the Web and is often structured only to a limited extent. Despite new inter- erability technologies such as XML and web services, integration of data is a highly di?cult and still largely manual task, especially due to the high degree of semantic heterogeneity and varying data quality as well as speci?c application requirements. The call for papers attracted many submissions on the workshop topics. - ter a carefulreviewing processthe internationalprogramcommittee accepted 13 long and 2 short papers which are included in this volume. They cover a wide spectrum of theoretical and practical issues including scienti?c/clinical wo- ?ows, ontologies, tools/systems, and integration techniques. DILS 2004 also f- tured two keynote presentations, by Dr. Thure Etzold (architect of the leading integration platform SRS, and president of Lion Bioscience, Cambridge, UK) and Prof. Dr. Svante Pa abo (Director, Max Planck Institute for Evolutionary Anthropology, Leipzig). The workshop took place during March 25 26, 2004, in Leipzig, Germany, and was organized by the Interdisciplinary Bioinformatics Center (IZBI) of the Universityof Leipzig.

Includes supplementary material: sn.pub/extras

Contenu
Scientific and Clinical Workflows.- An Ontology-Driven Framework for Data Transformation in Scientific Workflows.- PROVA: Rule-Based Java-Scripting for a Bioinformatics Semantic Web.- Process Based Data Logistics: a Solution for Clinical Integration Problems.- Ontologies and Taxonomies.- Domain-Specific Concepts and Ontological Reduction within a Data Dictionary Framework.- A Universal Character Model and Ontology of Defined Terms for Taxonomic Description.- On the Application of Formal Principles to Life Science Data: a Case Study in the Gene Ontology.- Indexing and Clustering.- Index-Driven XML Data Integration to Support Functional Genomics.- Heterogeneous Data Integration with the Consensus Clustering Formalism.- Integration Tools and Systems.- LinkSuiteTM: Formally Robust Ontology-Based Data and Information Integration.- BioDataServer: an Applied Molecular Biological Data Integration Service.- Columba: Multidimensional Data Integration of Protein Annotations.- Integration Techniques.- On the Integration of a Large Number of Life Science Web Databases.- Efficient Techniques to Explore and Rank Paths in Life Science Data Sources.- Links and Paths through Life Sciences Data Sources.- Pathway and Protein Interaction Data: from XML to FDM Database.