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Linking the Resource Description Framework to cheminformatics and proteochemometrics.

Willighagen EL, Alvarsson J, Andersson A, Eklund M, Lampa S, Lapins M, Spjuth O, Wikberg JE - J Biomed Semantics (2011)

Bottom Line: Ontologies and semantic markup have already been used for more than a decade in molecular sciences, but have not found widespread use yet.Being able to create and share workflows that integrate data aggregation and analysis (visual and statistical) is beneficial to interoperability and reproducibility.The current work shows that RDF approaches are sufficiently powerful to support molecular chemometrics workflows.

View Article: PubMed Central - HTML - PubMed

Affiliation: Uppsala University, Department of Pharmaceutical Biosciences, Box 591, SE-751 24 Uppsala, Sweden. egon.willighagen@farmbio.uu.se.

ABSTRACT

Background: Semantic web technologies are finding their way into the life sciences. Ontologies and semantic markup have already been used for more than a decade in molecular sciences, but have not found widespread use yet. The semantic web technology Resource Description Framework (RDF) and related methods show to be sufficiently versatile to change that situation.

Results: The work presented here focuses on linking RDF approaches to existing molecular chemometrics fields, including cheminformatics, QSAR modeling and proteochemometrics. Applications are presented that link RDF technologies to methods from statistics and cheminformatics, including data aggregation, visualization, chemical identification, and property prediction. They demonstrate how this can be done using various existing RDF standards and cheminformatics libraries. For example, we show how IC50 and Ki values are modeled for a number of biological targets using data from the ChEMBL database.

Conclusions: We have shown that existing RDF standards can suitably be integrated into existing molecular chemometrics methods. Platforms that unite these technologies, like Bioclipse, makes this even simpler and more transparent. Being able to create and share workflows that integrate data aggregation and analysis (visual and statistical) is beneficial to interoperability and reproducibility. The current work shows that RDF approaches are sufficiently powerful to support molecular chemometrics workflows.

No MeSH data available.


Related in: MedlinePlus

Screenshot of the http://rdf.openmolecules.net/ website for methane. It shows an RDF/XML document visualized by the browser with the associated XSLT stylesheet. Links are made to various resources, showing how the website can serve as hub for linking molecular data using the InChI.
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Figure 1: Screenshot of the http://rdf.openmolecules.net/ website for methane. It shows an RDF/XML document visualized by the browser with the associated XSLT stylesheet. Links are made to various resources, showing how the website can serve as hub for linking molecular data using the InChI.

Mentions: For example, Figure 1 shows the URI-based identifier for methane, http://rdf.openmolecules.net/?InChI=1/CH4/h1H4. The website does not primarily provide new data, but looks up information from other resources and links to those. In this way, it provides autogenerated RDF content for any InChI. These URIs makes it possible for any RDF database to use owl:sameAs triples to establish an InChI-based chemical identity for its molecules. Currently, the website acts as a hub in the Linked Data network: links are provided to ChEBI [40], NMRShiftDB [35], and DBPedia [41].


Linking the Resource Description Framework to cheminformatics and proteochemometrics.

Willighagen EL, Alvarsson J, Andersson A, Eklund M, Lampa S, Lapins M, Spjuth O, Wikberg JE - J Biomed Semantics (2011)

Screenshot of the http://rdf.openmolecules.net/ website for methane. It shows an RDF/XML document visualized by the browser with the associated XSLT stylesheet. Links are made to various resources, showing how the website can serve as hub for linking molecular data using the InChI.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3105498&req=5

Figure 1: Screenshot of the http://rdf.openmolecules.net/ website for methane. It shows an RDF/XML document visualized by the browser with the associated XSLT stylesheet. Links are made to various resources, showing how the website can serve as hub for linking molecular data using the InChI.
Mentions: For example, Figure 1 shows the URI-based identifier for methane, http://rdf.openmolecules.net/?InChI=1/CH4/h1H4. The website does not primarily provide new data, but looks up information from other resources and links to those. In this way, it provides autogenerated RDF content for any InChI. These URIs makes it possible for any RDF database to use owl:sameAs triples to establish an InChI-based chemical identity for its molecules. Currently, the website acts as a hub in the Linked Data network: links are provided to ChEBI [40], NMRShiftDB [35], and DBPedia [41].

Bottom Line: Ontologies and semantic markup have already been used for more than a decade in molecular sciences, but have not found widespread use yet.Being able to create and share workflows that integrate data aggregation and analysis (visual and statistical) is beneficial to interoperability and reproducibility.The current work shows that RDF approaches are sufficiently powerful to support molecular chemometrics workflows.

View Article: PubMed Central - HTML - PubMed

Affiliation: Uppsala University, Department of Pharmaceutical Biosciences, Box 591, SE-751 24 Uppsala, Sweden. egon.willighagen@farmbio.uu.se.

ABSTRACT

Background: Semantic web technologies are finding their way into the life sciences. Ontologies and semantic markup have already been used for more than a decade in molecular sciences, but have not found widespread use yet. The semantic web technology Resource Description Framework (RDF) and related methods show to be sufficiently versatile to change that situation.

Results: The work presented here focuses on linking RDF approaches to existing molecular chemometrics fields, including cheminformatics, QSAR modeling and proteochemometrics. Applications are presented that link RDF technologies to methods from statistics and cheminformatics, including data aggregation, visualization, chemical identification, and property prediction. They demonstrate how this can be done using various existing RDF standards and cheminformatics libraries. For example, we show how IC50 and Ki values are modeled for a number of biological targets using data from the ChEMBL database.

Conclusions: We have shown that existing RDF standards can suitably be integrated into existing molecular chemometrics methods. Platforms that unite these technologies, like Bioclipse, makes this even simpler and more transparent. Being able to create and share workflows that integrate data aggregation and analysis (visual and statistical) is beneficial to interoperability and reproducibility. The current work shows that RDF approaches are sufficiently powerful to support molecular chemometrics workflows.

No MeSH data available.


Related in: MedlinePlus