The BioRSTM Integration and Retrieval System: An open system for distributed data integration

Kaps, A.; Dyshlevoi, Konstantin; Heumann, Klaus G.; Jost, Ralf; Kontodinas, Ioannis; Wolff, Martin; Hani, Jean

doi:10.1515/jib-2006-44

“…This combines the advantages of a data-warehouse-based deep integration with the low maintenance costs of a federated environment. External information can be incorporated by using the embedded BioRS™Integration and Retrieval System [ 29 ] or by directly accessing external objects from e.g. a relational database, a web service or a software application.…”

Section: Methodsmentioning

confidence: 99%

Knowledge management for Systems Biology a general and visually driven framework applied to translational medicine

Maier

¹

,

Kalus

²

,

Wolff

³

et al. 2011

BMC Systems Biology

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BackgroundTo enhance our understanding of complex biological systems like diseases we need to put all of the available data into context and use this to detect relations, pattern and rules which allow predictive hypotheses to be defined. Life science has become a data rich science with information about the behaviour of millions of entities like genes, chemical compounds, diseases, cell types and organs, which are organised in many different databases and/or spread throughout the literature. Existing knowledge such as genotype - phenotype relations or signal transduction pathways must be semantically integrated and dynamically organised into structured networks that are connected with clinical and experimental data. Different approaches to this challenge exist but so far none has proven entirely satisfactory.ResultsTo address this challenge we previously developed a generic knowledge management framework, BioXM™, which allows the dynamic, graphic generation of domain specific knowledge representation models based on specific objects and their relations supporting annotations and ontologies. Here we demonstrate the utility of BioXM for knowledge management in systems biology as part of the EU FP6 BioBridge project on translational approaches to chronic diseases. From clinical and experimental data, text-mining results and public databases we generate a chronic obstructive pulmonary disease (COPD) knowledge base and demonstrate its use by mining specific molecular networks together with integrated clinical and experimental data.ConclusionsWe generate the first semantically integrated COPD specific public knowledge base and find that for the integration of clinical and experimental data with pre-existing knowledge the configuration based set-up enabled by BioXM reduced implementation time and effort for the knowledge base compared to similar systems implemented as classical software development projects. The knowledgebase enables the retrieval of sub-networks including protein-protein interaction, pathway, gene - disease and gene - compound data which are used for subsequent data analysis, modelling and simulation. Pre-structured queries and reports enhance usability; establishing their use in everyday clinical settings requires further simplification with a browser based interface which is currently under development.

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“…To optimize performance, data can be managed alternatively within a relational database or integrated from external data sources, combining the advantages of the data warehouse and the federated approach. The federation of external data sources uses the Biomax software BioRS [107].…”

Section: Federated Examplesmentioning

confidence: 99%

Biomedical Data Integration in Computational Drug Design and Bioinformatics

Seoane¹,

Aguiar‐Pulido²,

Munteanu³

et al. 2013

CAD

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In recent years, in the post genomic era, more and more data is being generated by biological high throughput technologies, such as proteomics and transcriptomics. This omics data can be very useful, but the real challenge is to analyze all this data, as a whole, after integrating it. Biomedical data integration enables making queries to different, heterogeneous and distributed biomedical data sources. Data integration solutions can be very useful not only in the context of drug design, but also in biomedical information retrieval, clinical diagnosis, system biology, etc. In this review, we analyze the most common approaches to biomedical data integration, such as federated databases, data warehousing, multi-agent systems and semantic technology, as well as the solutions developed using these approaches in the past few years.

show abstract

“…To optimize performance, data can be managed alternatively within a relational database or integrated from external data sources, combining the advantages of the data warehouse and the federated approach. The federation of external data sources uses the Biomax software BioRS [107].…”

Section: Federated Examplesmentioning

confidence: 99%

Biomedical Data Integration in Computational Drug Design and Bioinformatics

Seoane¹,

Aguiar‐Pulido²,

Munteanu³

et al. 2013

Current Computer - Aided Drug Design

View full text Add to dashboard Cite

In recent years, in the post genomic era, more and more data is being generated by biological high throughput technologies, such as proteomics and transcriptomics. This omics data can be very useful, but the real challenge is to analyze all this data, as a whole, after integrating it. Biomedical data integration enables making queries to different, heterogeneous and distributed biomedical data sources. Data integration solutions can be very useful not only in the context of drug design, but also in biomedical information retrieval, clinical diagnosis, system biology, etc. In this review, we analyze the most common approaches to biomedical data integration, such as federated databases, data warehousing, multi-agent systems and semantic technology, as well as the solutions developed using these approaches in the past few years.

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The BioRSTM Integration and Retrieval System: An open system for distributed data integration

Cited by 7 publications

References 11 publications

Knowledge management for Systems Biology a general and visually driven framework applied to translational medicine

Knowledge management for Systems Biology a general and visually driven framework applied to translational medicine

Biomedical Data Integration in Computational Drug Design and Bioinformatics

Biomedical Data Integration in Computational Drug Design and Bioinformatics

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