An ontology for bioinformatics applications.

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

doi:10.1093/bioinformatics/15.6.510

Cited by 173 publications

(84 citation statements)

References 16 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…However, these ontologies are biological ontologies used mainly as controlled vocabularies for data annotations, and are not resource ontologies. Developments in bioinformatics resource ontologies have begun to emerge in recent years in projects such as myGrid [13] and the defunct TAMBIS (Transparent Access to Multiple Bioinformatics Information Sources) Ontology [22,23]. Developments such as these, integrated with more generic online resource frameworks such as the World-Wide-Web Consortium's (W3C) projects into resource description and resource discovery standards (http://www.w3.org/RDF/), are important progress towards proper bioinformatics resource ontologies.…”

Section: Discussionmentioning

confidence: 99%

A Bioinformatics Reference Model: Towards a Framework for Developing and Organising Bioinformatic Resources

Hiew¹,

Bellgard²

2007

AIP Conference Proceedings

View full text Add to dashboard Cite

Abstract. Life Science research faces the constant challenge of how to effectively handle an ever-growing body of bioinformatics software and online resources. The users and developers of bioinformatics resources have a diverse set of competing demands on how these resources need to be developed and organised. Unfortunately, there does not exist an adequate community-wide framework to integrate such competing demands. The problems that arise from this include unstructured standards development, the emergence of tools that do not meet specific needs of researchers, and often times a communications gap between those who use the tools and those who supply them. This paper presents an overview of the different functions and needs of bioinformatics stakeholders to determine what may be required in a community-wide framework. A Bioinformatics Reference Model is proposed as a basis for such a framework. The reference model outlines the functional relationship between research usage and technical aspects of bioinformatics resources. It separates important functions into multiple structured layers, clarifies how they relate to each other, and highlights the gaps that need to be addressed for progress towards a diverse, manageable, and sustainable body of resources. The relevance of this reference model to the bioscience research community, and its implications in progress for organising our bioinformatics resources, are discussed.

show abstract

Section: Discussionmentioning

confidence: 99%

A Bioinformatics Reference Model: Towards a Framework for Developing and Organising Bioinformatic Resources

Hiew¹,

Bellgard²

2007

AIP Conference Proceedings

View full text Add to dashboard Cite

show abstract

“…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%

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

Mougin

Burgun

Bodenreider

et al. 2008

Lecture Notes in Computer Science

View full text Add to dashboard Cite

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.

show abstract

“…The TAM-BIS ontology (Baker et al 1999) and the myGrid ontology (Wroe et al 2003) are examples of ontologies that are intended to create categorizations of concepts and relationships. For example, TAMBIS categorizes representations of biological structures into "physical" and "abstract."…”

Section: Ontologies To Support Shared Knowledgementioning

confidence: 99%

CI-Miner: semantically enhancing scientific processes

et al. 2009

View full text Add to dashboard Cite

The realization of an international cyberinfrastructure of shared resources to overcome time and space limitations is challenging scientists to rethink how to document their processes. Many known scientific process requirements that would normally be considered impossible to implement a few years ago are close to becoming a reality for scientists, such as large scale integration and data reuse, data sharing across distinct scientific domains, comprehensive support for explaining process results, and full search capability for scientific products across domains. This article introduces the CI-Miner approach that can be used to aggregate knowledge about scientific processes and their products through the use of semantic annotations. The article shows how this aggregated knowledge is used to benefit scientists during the development of their research activities. The discussion is grounded on lessons learned through the use of CI-Miner to semantically annotate scientific processes in the areas of geo-sciences,

show abstract

An ontology for bioinformatics applications.

Cited by 173 publications

References 16 publications

A Bioinformatics Reference Model: Towards a Framework for Developing and Organising Bioinformatic Resources

A Bioinformatics Reference Model: Towards a Framework for Developing and Organising Bioinformatic Resources

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

CI-Miner: semantically enhancing scientific processes

Contact Info

Product

Resources

About