http://precedings.nature.com/tags/ontologies Recently posted documents tagged with 'ontologies' Nature Publishing Group en Nature Precedings http://precedings.nature.com/images/header_logo.gif http://precedings.nature.com http://precedings.nature.com/documents/3938/version/1 Two of the most significant formats for biomedical ontologies are the Open Biomedical Ontologies Format (OBOF) and the Web Ontology Language (OWL). To make it possible to translate ontologies between these two representation formats, the National Center for Biomedical Ontology (NCBO) has developed a mapping between the OBOF and OWL formats as well as inter-conversion software. The goal was to allow the sharing of tools, ontologies, and associated data between the OBOF and Semantic Web communities.OBOF does not have a formal grammar, so the NCBO had to capture its intended semantics to map it to OWL.This official NCBO mapping was used to make all OBO Foundry ontologies available in OWL. Availability: This mapping functionality can be embedded into OBO-Edit and Protégé-OWL ontology editors. This software is available at: http://bioontology.org/wiki/index.php/OboInOwl:Main_Page http://precedings.nature.com/documents/3938/version/1 Wed, 04 Nov 2009 16:35:19 UTC The NCBO OBOF to OWL Mapping hdl:10101/npre.2009.3938.1 2009-11-04 Dilvan A. Moreira Nature Precedings 2009-11-04T16:35:19Z Manuscript Bioinformatics http://creativecommons.org/licenses/by/3.0/ http://dx.doi.org/10.1038/npre.2009.3646.1 This project aims to reach a philosophical understanding of the role played by theory in the practices of data dissemination and re-use that characterise data-driven research. Bio-ontologies have the potential to play the epistemic role of theories in this context, insofar as they (1) express the knowledge underlying data-driven research and (2) guide such research towards future discoveries. http://dx.doi.org/10.1038/npre.2009.3646.1 Tue, 18 Aug 2009 15:46:19 UTC The Role of Bio-Ontologies in Data-Driven Research: A Philosophical Perspective doi:10.1038/npre.2009.3646.1 2009-08-18 Sabina Leonelli Nature Precedings 2009-08-18T15:46:19Z Poster Bioinformatics http://creativecommons.org/licenses/by/3.0/ http://precedings.nature.com/documents/3574/version/1 While the Web Ontology Language (OWL) provides a mechanism to import ontologies, this mechanism is not always suitable. First, given the current state of editing tools and the issues they have working with large ontologies, direct OWL imports have sometimes proven impractical for day-to-day development. Second, ontologies chosen for integration may be under active development and not aligned with the chosen design principles. Importing heterogeneous ontologies in their entirety may lead to inconsistencies or unintended inferences. In this paper we propose a set of guidelines for importing required terms from an external resource into a target ontology. We describe the guidelines, their implementation, present some examples of application, and outline future work and extensions. http://precedings.nature.com/documents/3574/version/1 Mon, 10 Aug 2009 15:16:25 UTC MIREOT: the Minimum Information to Reference an External Ontology Term hdl:10101/npre.2009.3574.1 2009-08-10 Melanie Courtot Nature Precedings 2009-08-10T15:16:25Z Manuscript Biotechnology Bioinformatics http://creativecommons.org/licenses/by/3.0/ http://dx.doi.org/10.1038/npre.2009.3576.1 While the Web Ontology Language (OWL) provides a mechanism to import ontologies, this mechanism is not always suitable. First, given the current state of editing tools and the issues they have working with large ontologies, direct OWL imports have sometimes proven impractical for day-to-day development. Second, ontologies chosen for integration may be under active development and not aligned with the chosen design principles. Importing heterogeneous ontologies in their entirety may lead to inconsistencies or unintended inferences. In this paper we propose a set of guidelines for importing required terms from an external resource into a target ontology. We describe the guidelines, their implementation, present some examples of application, and outline future work and extensions. http://dx.doi.org/10.1038/npre.2009.3576.1 Mon, 10 Aug 2009 14:42:27 UTC MIREOT: the Minimum Information to Reference an External Ontology Term doi:10.1038/npre.2009.3576.1 2009-08-10 Mélanie Courtot Nature Precedings 2009-08-10T14:42:27Z Presentation Biotechnology Bioinformatics http://creativecommons.org/licenses/by/3.0/ http://precedings.nature.com/documents/3562/version/1 While OWL, the Web Ontology Language, is often regarded as the preferred language for Knowledge Representation in the world of the Semantic Web, the potential of direct representation in RDF, the Resource Description Framework, is underestimated. Here we show how ontologies adequately represented in RDF could be semantically enriched with SPARUL. To deal with the semantics of relations we created Metarel, a meta-ontology for relations. The utility of the approach is demonstrated by an application on Gene Ontology Annotation (GOA) RDF graphs in the RDF Knowledge Base BioGateway. We show that Metarel can facilitate inferencing in BioGateway, which allows for queries that are otherwise not possible. Metarel is available on http://www.metarel.org. http://precedings.nature.com/documents/3562/version/1 Thu, 06 Aug 2009 19:10:14 UTC Metarel: an Ontology to support the inferencing of Semantic Web relations within Biomedical Ontologies hdl:10101/npre.2009.3562.1 2009-08-06 Ward Blondé Nature Precedings 2009-08-06T19:10:14Z Manuscript Genetics & Genomics Bioinformatics http://creativecommons.org/licenses/by/3.0/ http://dx.doi.org/10.1038/npre.2009.3546.1 The anatomy of model species is described in ontologies, which are used to standardize the annotations of experimental data, such as gene expression patterns. To compare such data between species, we aim to establish homology relations between ontologies describing different species. We present a new algorithm, and its implementation in the software Homolonto, to create new relationships between anatomical ontologies, based on the homology concept. These relationships and the Homolonto software are available at http://bgee.unil.ch/ http://dx.doi.org/10.1038/npre.2009.3546.1 Wed, 05 Aug 2009 19:01:14 UTC Generating Homology Relationships by Alignment of Anatomical Ontologies doi:10.1038/npre.2009.3546.1 2009-08-05 Frederic Bastian Nature Precedings 2009-08-05T19:01:14Z Presentation Bioinformatics http://creativecommons.org/licenses/by/3.0/ http://dx.doi.org/10.1038/npre.2009.3522.1 Formal knowledge about human anatomy, radiology or diseases is necessary to support clinical applications such as medical image search. This machine processable knowledge can be acquired from biomedical domain ontologies, which however, are typically very large and complex models. Thus, their straightforward incorporation into the software applications becomes difficult. In this paper we discuss first ideas on a statistical approach for modularizing large medical ontologies and we prioritize the practical applicability aspect. The underlying assumption is that the application relevant ontology fragments, i.e. modules, can be identified by the statistical analysis of the ontology concepts in the domain corpus. Accordingly, we argue that most frequently occurring concepts in the domain corpus define the application context and can therefore potentially yield the relevant ontology modules. We illustrate our approach on an example case that involves a large ontology on human anatomy and report on our first manual experiments. http://dx.doi.org/10.1038/npre.2009.3522.1 Thu, 30 Jul 2009 19:39:18 UTC Towards Context Driven Modularization of Large Biomedical Ontologies doi:10.1038/npre.2009.3522.1 2009-07-30 Pinar Wennerberg Nature Precedings 2009-07-30T19:39:18Z Manuscript Bioinformatics http://creativecommons.org/licenses/by/3.0/ http://dx.doi.org/10.1038/npre.2009.3523.1 Formal knowledge about human anatomy, radiology or diseases is necessary to support clinical applications such as medical image search. This machine processable knowledge can be acquired from biomedical domain ontologies, which however, are typically very large and complex models. Thus, their straightforward incorporation into the software applications becomes difficult. In this paper we discuss first ideas on a statistical approach for modularizing large medical ontologies and we prioritize the practical applicability aspect. The underlying assumption is that the application relevant ontology fragments, i.e. modules, can be identified by the statistical analysis of the ontology concepts in the domain corpus. Accordingly, we argue that most frequently occurring concepts in the domain corpus define the application context and can therefore potentially yield the relevant ontology modules. We illustrate our approach on an example case that involves a large ontology on human anatomy and report on our first manual experiments. http://dx.doi.org/10.1038/npre.2009.3523.1 Thu, 30 Jul 2009 19:38:16 UTC Towards Context Driven Modularization of Large Biomedical Ontologies doi:10.1038/npre.2009.3523.1 2009-07-30 Pinar Wennerberg Nature Precedings 2009-07-30T19:38:16Z Presentation Bioinformatics http://creativecommons.org/licenses/by/3.0/ http://dx.doi.org/10.1038/npre.2009.3502.1 This article discusses an ontology-handling technology to provide on-demand reorganization of is-a hierarchy of diseases instead of one fixed hierarchy to cope with various viewpoints which physicians might have. It is one of the important benefits of our medical ontology which is developed as a Japanese national project. This technology tackles with the multi-perspective issues of medical knowledge. http://dx.doi.org/10.1038/npre.2009.3502.1 Wed, 29 Jul 2009 19:17:40 UTC Dynamic is-a Hierarchy Generation from a Clinical Medical Ontology doi:10.1038/npre.2009.3502.1 2009-07-29 Kouji Kozaki Nature Precedings 2009-07-29T19:17:40Z Presentation Bioinformatics http://creativecommons.org/licenses/by/3.0/ http://dx.doi.org/10.1038/npre.2009.3458.1 We describe a first-generation ontology forrepresentation and integration of event-related brain potentials (ERPs). The ontology is designed following OBO “best practices” and is augmented with tools to perform ontology-based labeling and annotation of ERP data, and a database that enables semantically based reasoning over these data. Because certain high-level concepts in the ERP domain are illdefined, we have developed methods to support coordinated updates to each of these three components. This approach consists of “top-down” (knowledge-driven) design and implementation, followed by “bottom-up” (data-driven) validation and refinement. Our goal is to build an ERP ontology that is logically valid, empirically sound, robust in application, and transparent to users. This ontology will be used to support sharing and meta-analysis of EEG and MEG data collected within our Neural Electromagnetic Ontologies (NEMO) project. http://dx.doi.org/10.1038/npre.2009.3458.1 Fri, 24 Jul 2009 20:57:40 UTC Development of Neural Electromagnetic Ontologies (NEMO): Ontology-based Tools for Representation and Integration of Event-related Brain Potentials doi:10.1038/npre.2009.3458.1 2009-07-24 Gwen A. Frishkoff Nature Precedings 2009-07-24T20:57:40Z Manuscript Neuroscience Bioinformatics http://creativecommons.org/licenses/by/3.0/