TAMBIS: Transparent Access to Multiple Bioinformatics
  Information Sources

Baker, Peter; Brass, Andy; Bechhofer, Sean; Goble, Carole; Paton, Norman W.; Stevens, Robert

doi:10.1093/bioinformatics/16.2.184

Cited by 292 publications

(137 citation statements)

References 10 publications

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“…Among the data sources frequently used by biologists, and based on these criteria, we selected the following eleven biomedical sources for integration in our system: • genomic sources: GeneCards 1 , Entrez Gene 2 , Geneloc 3 , HGNC 4 , HGMD 5 , and MGI 6 ; • protein sources: Swiss-Prot 7 , PDB 8 , HPRD 9 , Interpro 10 ;…”

Section: Methodsmentioning

confidence: 99%

“…Most existing biomedical mediator-based systems developed their own ontology, so that it suits exactly the requirements for the global schema of the integration system. For example, the developers of TAMBIS [4] created the ontology TAO [17], and designed it specifically to function as the global schema of the TAMBIS system. In contrast, we reused an independently-developed, multi-purpose terminological system, the UMLS.…”

Section: Contribution Of the Proposed Methodsmentioning

confidence: 99%

“…This is a key issue that has not been addressed by existing integration systems such as TAMBIS [4], BioMediator [20], and BACIIS [21]. This approach is useful during the query process, when the mediator consolidates the results obtained from each source.…”

Section: Contribution Of the Proposed Methodsmentioning

confidence: 99%

“…• with mediator-based systems, e.g., TAMBIS [4], data sources are queried dynamically. This approach guarantees that users access up-to-date information, because only the schemas of the sources (or local schemas) are stored in the system.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Automatic Methods for Integrating Biomedical Data Sources in a Mediator-Based System

Mougin

Burgun

Bodenreider

et al. 2008

Lecture Notes in Computer Science

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Abstract. The information needed by biologists and physicians for research purposes is distributed over many heterogeneous sources. Integration systems provide a single, centralized and homogeneous interface for users to query multiple information sources simultaneously. The major limitation of integration systems, including mediator-based systems, is that the tasks involved in their creation and maintenance remain mainly manual. To address this limitation, we developed automated methods for facilitating the creation of a mediator-based system. We first implemented an automatic method for acquiring the local schemas of the sources to be integrated. We derived the global schema from the UMLS. Finally, we proposed schema-and instance-based approaches to mapping data elements from the local schemas to the global schema. To illustrate the applicability of our methods, we created a mediator-based system integrating eleven biomedical sources. This prototype is operational, available on the Internet (http://www.med.univ-rennes1.fr/cgi-bin/mougin/These/system.pl) and its evolution is managed semi-automatically.

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Section: Methodsmentioning

confidence: 99%

Section: Contribution Of the Proposed Methodsmentioning

confidence: 99%

Section: Contribution Of the Proposed Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Automatic Methods for Integrating Biomedical Data Sources in a Mediator-Based System

Mougin

Burgun

Bodenreider

et al. 2008

Lecture Notes in Computer Science

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“…Data and information integration and retrieval is essential for studying gene networks, and although several solutions for this already exist (e.g. BioRS 3 , SRS 4 ; also some ontology-based solutions like TAMBIS [25] and caBIO [8]. A particular challenge is the development of a specific cell-cycle ontology (CCO), as this is relatively poorly developed at present.…”

Section: Introductionmentioning

confidence: 99%

A Cell-Cycle Knowledge Integration Framework

Antezana

Tsiporkova

Mironov

et al. 2006

Lecture Notes in Computer Science

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Abstract. The goal of the EU FP6 project DIAMONDS 1 is to build a computational platform for studying the cell-cycle regulation process in several different (model) organisms (S. cerevisiae, S. pombe, A. thaliana and human). This platform will enable wet-lab biologists to use a systems biology approach encompassing data integration, modeling and simulation, thereby supporting analysis and interpretation of biochemical pathways involved in the cell cycle. To facilitate the computational handling of cell-cycle specific knowledge a detailed cell-cycle ontology is essential. The currently existing cell-cycle branch of the Gene Ontology (GO) provides only a static view and it is not rich enough to support in-depth cell-cycle studies.In this work, an enhanced Cell-Cycle Ontology (CCO) is proposed as an extension to existing GO. Besides the classical add-ons given by an ontology (data repository, knowledge sharing, validation, annotation, and so on), CCO is intended to further evolve into a knowledge-based system that provides reasoning services oriented to hypotheses evaluation in the context of cell-cycle studies. A data integration pipeline prototype, covering the entire life cycle of the knowledge base, is presented. Concrete problems and initial results related to the implementation of automatic format mappings between ontologies and inconsistency checking issues are discussed in detail.

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Sequence and Genome Bioinformatics

Mewes¹

2003

Handbook of Chemoinformatics

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TAMBIS: Transparent Access to Multiple Bioinformatics Information Sources

Abstract: tambis@cs.man.ac.uk

Cited by 292 publications

References 10 publications

Automatic Methods for Integrating Biomedical Data Sources in a Mediator-Based System

Automatic Methods for Integrating Biomedical Data Sources in a Mediator-Based System

A Cell-Cycle Knowledge Integration Framework

Sequence and Genome Bioinformatics

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