| 1. |
- Hardy, Barry, et al.
(författare)
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Toxicology Ontology Perspectives
- 2012
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Ingår i: ALTEX. Alternatives zu Tierexperimenten. - 0946-7785. ; 29:2, s. 139-156
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Tidskriftsartikel (refereegranskat)abstract
- The field of predictive toxicology requires the development of open, public, computable, standardized toxicology vocabularies and ontologies to support the applications required by in silico, in vitro, and in vivo toxicology methods and related analysis and reporting activities. In this article we review ontology developments based on a set of perspectives showing how ontologies are being used in predictive toxicology initiatives and applications. Perspectives on resources and initiatives reviewed include OpenTox, eTOX, Pistoia Alliance, ToxWiz, Virtual Liver, EU-ADR, BEL, ToxML, and Bioclipse. We also review existing ontology developments in neighboring fields that can contribute to establishing an ontological framework for predictive toxicology. A significant set of resources is already available to provide a foundation for an ontological framework for 21st century mechanistic-based toxicology research. Ontologies such as ToxWiz provide a basis for application to toxicology investigations, whereas other ontologies under development in the biological, chemical, and biomedical communities could be incorporated in an extended future framework. OpenTox has provided a semantic web framework for the implementation of such ontologies into software applications and linked data resources. Bioclipse developers have shown the benefit of interoperability obtained through ontology by being able to link their workbench application with remote OpenTox web services. Although these developments are promising, an increased international coordination of efforts is greatly needed to develop a more unified, standardized, and open toxicology ontology framework.
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| 2. |
- Harry, Barry, et al.
(författare)
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Food for thought... : A toxicology ontology roadmap
- 2012
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Ingår i: ALTEX. Alternatives zu Tierexperimenten. - 0946-7785. ; 29:2, s. 129-137
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Tidskriftsartikel (refereegranskat)abstract
- Foreign substances can have a dramatic and unpredictable adverse effect on human health. In the development of new therapeutic agents, it is essential that the potential adverse effects of all candidates be identified as early as possible. The field of predictive toxicology strives to profile the potential for adverse effects of novel chemical substances before they occur, both with traditional in vivo experimental approaches and increasingly through the development of in vitro and computational methods which can supplement and reduce the need for animal testing. To be maximally effective, the field needs access to the largest possible knowledge base of previous toxicology findings, and such results need to be made available in such a fashion so as to be interoperable, comparable, and compatible with standard toolkits. This necessitates the development of open, public, computable, and standardized toxicology vocabularies and ontologies so as to support the applications required by in silico, in vitro, and in vivo toxicology methods and related analysis and reporting activities. Such ontology development will support data management, model building, integrated analysis, validation and reporting, including regulatory reporting and alternative testing submission requirements as required by guidelines such as the REACH legislation, leading to new scientific advances in a mechanistically-based predictive toxicology. Numerous existing ontology and standards initiatives can contribute to the creation of a toxicology ontology supporting the needs of predictive toxicology and risk assessment. Additionally, new ontologies are needed to satisfy practical use cases and scenarios where gaps currently exist. Developing and integrating these resources will require a well-coordinated and sustained effort across numerous stakeholders engaged in a public-private partnership. In this communication, we set out a roadmap for the development of an integrated toxicology ontology, harnessing existing resources where applicable. We describe the stakeholders’ requirements analysis from the academic and industry perspectives, timelines, and expected benefits of this initiative, with a view to engagement with the wider community.
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| 3. |
- Hastings, Janna, et al.
(författare)
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The Chemical Information Ontology : provenance and disambiguation for chemical data on the biological Semantic Web
- 2011
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Ingår i: PLOS ONE. - : Public Library of Science (PLoS). - 1932-6203. ; 6:10, s. e25513-
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Tidskriftsartikel (refereegranskat)abstract
- Cheminformatics is the application of informatics techniques to solve chemical problems in silico. There are many areas in biology where cheminformatics plays an important role in computational research, including metabolism, proteomics, and systems biology. One critical aspect in the application of cheminformatics in these fields is the accurate exchange of data, which is increasingly accomplished through the use of ontologies. Ontologies are formal representations of objects and their properties using a logic-based ontology language. Many such ontologies are currently being developed to represent objects across all the domains of science. Ontologies enable the definition, classification, and support for querying objects in a particular domain, enabling intelligent computer applications to be built which support the work of scientists both within the domain of interest and across interrelated neighbouring domains. Modern chemical research relies on computational techniques to filter and organise data to maximise research productivity. The objects which are manipulated in these algorithms and procedures, as well as the algorithms and procedures themselves, enjoy a kind of virtual life within computers. We will call these information entities. Here, we describe our work in developing an ontology of chemical information entities, with a primary focus on data-driven research and the integration of calculated properties (descriptors) of chemical entities within a semantic web context. Our ontology distinguishes algorithmic, or procedural information from declarative, or factual information, and renders of particular importance the annotation of provenance to calculated data. The Chemical Information Ontology is being developed as an open collaborative project.
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| 4. |
- Rocca-Serra, Philippe, et al.
(författare)
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Data standards can boost metabolomics research, and if there is a will, there is a way
- 2016
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Ingår i: Metabolomics. - New York; USA : Springer-Verlag New York. - 1573-3882 .- 1573-3890. ; 12
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Tidskriftsartikel (refereegranskat)abstract
- Thousands of articles using metabolomics approaches are published every year. With the increasing amounts of data being produced, mere description of investigations as text in manuscripts is not sufficient to enable re-use anymore: the underlying data needs to be published together with the findings in the literature to maximise the benefit from public and private expenditure and to take advantage of an enormous opportunity to improve scientific reproducibility in metabolomics and cognate disciplines. Reporting recommendations in metabolomics started to emerge about a decade ago and were mostly concerned with inventories of the information that had to be reported in the literature for consistency. In recent years, metabolomics data standards have developed extensively, to include the primary research data, derived results and the experimental description and importantly the metadata in a machine-readable way. This includes vendor independent data standards such as mzML for mass spectrometry and nmrML for NMR raw data that have both enabled the development of advanced data processing algorithms by the scientific community. Standards such as ISA-Tab cover essential metadata, including the experimental design, the applied protocols, association between samples, data files and the experimental factors for further statistical analysis. Altogether, they pave the way for both reproducible research and data reuse, including meta-analyses. Further incentives to prepare standards compliant data sets include new opportunities to publish data sets, but also require a little "arm twisting" in the author guidelines of scientific journals to submit the data sets to public repositories such as the NIH Metabolomics Workbench or MetaboLights at EMBL-EBI. In the present article, we look at standards for data sharing, investigate their impact in metabolomics and give suggestions to improve their adoption.
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| 5. |
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| 6. |
- Spjuth, Ola, 1977-, et al.
(författare)
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Harmonising and linking biomedical and clinical data across disparate data archives to enable integrative cross-biobank research
- 2016
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Ingår i: European Journal of Human Genetics. - : Springer Science and Business Media LLC. - 1018-4813 .- 1476-5438. ; 24:4, s. 521-528
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Tidskriftsartikel (refereegranskat)abstract
- A wealth of biospecimen samples are stored in modern globally distributed biobanks. Biomedical researchers worldwide need to be able to combine the available resources to improve the power of large-scale studies. A prerequisite for this effort is to be able to search and access phenotypic, clinical and other information about samples that are currently stored at biobanks in an integrated manner. However, privacy issues together with heterogeneous information systems and the lack of agreed-upon vocabularies have made specimen searching across multiple biobanks extremely challenging. We describe three case studies where we have linked samples and sample descriptions in order to facilitate global searching of available samples for research. The use cases include the ENGAGE (European Network for Genetic and Genomic Epidemiology) consortium comprising at least 39 cohorts, the SUMMIT (surrogate markers for micro- and macro-vascular hard endpoints for innovative diabetes tools) consortium and a pilot for data integration between a Swedish clinical health registry and a biobank. We used the Sample avAILability (SAIL) method for data linking: first, created harmonised variables and then annotated and made searchable information on the number of specimens available in individual biobanks for various phenotypic categories. By operating on this categorised availability data we sidestep many obstacles related to privacy that arise when handling real values and show that harmonised and annotated records about data availability across disparate biomedical archives provide a key methodological advance in pre-analysis exchange of information between biobanks, that is, during the project planning phase.
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| 7. |
- Willighagen, Egon L, et al.
(författare)
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The ChEMBL database as linked open data
- 2013
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Ingår i: Journal of Cheminformatics. - : Springer Science and Business Media LLC. - 1758-2946. ; 5:1, s. 23-
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Tidskriftsartikel (refereegranskat)abstract
- Background: Making data available as Linked Data using Resource Description Framework (RDF) promotes integration with other web resources. RDF documents can natively link to related data, and others can link back using Uniform Resource Identifiers (URIs). RDF makes thedata machine-readable and uses extensible vocabularies for additional information, making it easier to scale up inference and data analysis. Results: This paper describes recent developments in an ongoing project converting data from the ChEMBL database into RDF triples. Relative to earlier versions, this updated version of ChEMBL-RDF uses recently introduced ontologies, including CHEMINF and CiTO; exposes more information from the database; and is now available as dereferencable,linked data. To demonstrate these new features, we present novel use cases showing further integration with other web resources, including Bio2RDF, Chem2Bio2RDF, and ChemSpider, and showing the use of standard ontologies for querying. Conclusions: We have illustrated the advantages of using open standards and ontologies to link the ChEMBL database to other databases. Using those links and the knowledge encoded in standards and ontologies, theChEMBL-RDF resource creates a foundation for integrated semantic web cheminformatics applications, such as the presented decision support.
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