Titlebook: Data Integration in the Life Sciences; Second International Bertram Lud?scher,Louiqa Raschid Conference proceedings 2005 Springer-Verlag Be

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Integrating Heterogeneous Microarray Data Sources Using Correlation Signaturesf microarray gene expression profiles based on different tissues, species, and conditions. Combining such vast amount of microarray data sets is an important and yet challenging problem. In this paper, we introduce a “correlation signature” method that allows the coherent interpretation and integrat

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Knowledge-Based Integrative Framework for Hypothesis Formation in Biochemical Networksrevision or extension are first formulated as theoretical hypotheses, then verified experimentally. Recently, biological data have been produced in great volumes and in diverse formats. It is a major challenge for biologists to process these data to reason about hypotheses. Many computer-aided syste

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Assigning Unique Keys to Chemical Compounds for Data Integration: Some Interesting Counter Exampleshese identifiers can be used as database keys. One common approach is to use the Unique SMILES notation introduced in [2]. The Unique SMILES views a chemical structure as a graph with atoms as nodes and bonds as edges and uses a depth first traversal of the graph to generate the SMILES strings. The

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Information Integration and Knowledge Acquisition from Semantically Heterogeneous Biological Data Somantically heterogeneous data sources that can be viewed (conceptually) as tables. INDUS employs ontologies and inter-ontology mappings, to enable a user or an application to view a collection of such data sources (regardless of location, internal structure and query interfaces) as though they were

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Cluster Based Integration of Heterogeneous Biological Databases Using the AutoMed Toolkit a clustering approach has been developed to support distributed biological data sources with inconsistent identification of biological objects. The architecture uses the AutoMed data integration toolkit to store the schemas of the data sources and the semi-automatically generated transformations fr

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Hybrid Integration of Molecular-Biological Annotation Dataialized in a data warehouse supporting high performance for data-intensive analysis tasks. On the other hand, annotation data is integrated virtually according to analysis needs. Our virtual integration utilizes the commercial product SRS (Sequence Retrieval System) of LION bioscience. To couple the

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