Data Integration in the Life Sciences

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.