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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

A Bioclipse script showing the use of the SWI-Prolog functionality to load inline Prolog code. It uses the loadPrologCode() method, load RDF data with the loadRDFToProlog() method, and query the RDF knowledge base as then defined in the Prolog environment. This particular script searches spectra with a shift near 42.2 ppm. Available from additional file 9.
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Figure 17: A Bioclipse script showing the use of the SWI-Prolog functionality to load inline Prolog code. It uses the loadPrologCode() method, load RDF data with the loadRDFToProlog() method, and query the RDF knowledge base as then defined in the Prolog environment. This particular script searches spectra with a shift near 42.2 ppm. Available from additional file 9.

Mentions: This approach is used in the script shown in Figure 17 where an RDF file is loaded into the Prolog environment. A Prolog predicate is there defined and then used to query for molecules which have a spectrum with a peak shift matching the given value. The resulting molecules are then returned, where they can be opened in a molecules table, if desired, as demonstrated in some of the earlier examples by using the SMILES for the found molecules.


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)

A Bioclipse script showing the use of the SWI-Prolog functionality to load inline Prolog code. It uses the loadPrologCode() method, load RDF data with the loadRDFToProlog() method, and query the RDF knowledge base as then defined in the Prolog environment. This particular script searches spectra with a shift near 42.2 ppm. Available from additional file 9.
© Copyright Policy - open-access
Related In: Results  -  Collection

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

Figure 17: A Bioclipse script showing the use of the SWI-Prolog functionality to load inline Prolog code. It uses the loadPrologCode() method, load RDF data with the loadRDFToProlog() method, and query the RDF knowledge base as then defined in the Prolog environment. This particular script searches spectra with a shift near 42.2 ppm. Available from additional file 9.
Mentions: This approach is used in the script shown in Figure 17 where an RDF file is loaded into the Prolog environment. A Prolog predicate is there defined and then used to query for molecules which have a spectrum with a peak shift matching the given value. The resulting molecules are then returned, where they can be opened in a molecules table, if desired, as demonstrated in some of the earlier examples by using the SMILES for the found molecules.

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