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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 DBPedia entries with SMILES in Bioclipse. The data was retrieved with SPARQL and shown in a molecules table by a Bioclipse script (see Figure 7).
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Figure 6: Screenshot of DBPedia entries with SMILES in Bioclipse. The data was retrieved with SPARQL and shown in a molecules table by a Bioclipse script (see Figure 7).

Mentions: We demonstrate the visualization capabilities using a Bioclipse script that queries the SPARQL end point of DBPedia, a RDF database with the structured data from Wikipedia [43]. The script queries all entries that have a SMILES, because those are far more abundant than InChIs in Wikipedia, and it uses the CDK to create an MDL SD file, while storing the DBPedia resource URI as property. Clearly, any chemical property can be calculated on the fly, or looked up via additional RDF sources, as is done in the previous example. The results are then opened in a JChemPaint-based molecule table functionality in Bioclipse, as shown in Figure 6.


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 DBPedia entries with SMILES in Bioclipse. The data was retrieved with SPARQL and shown in a molecules table by a Bioclipse script (see Figure 7).
© Copyright Policy - open-access
Related In: Results  -  Collection

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

Figure 6: Screenshot of DBPedia entries with SMILES in Bioclipse. The data was retrieved with SPARQL and shown in a molecules table by a Bioclipse script (see Figure 7).
Mentions: We demonstrate the visualization capabilities using a Bioclipse script that queries the SPARQL end point of DBPedia, a RDF database with the structured data from Wikipedia [43]. The script queries all entries that have a SMILES, because those are far more abundant than InChIs in Wikipedia, and it uses the CDK to create an MDL SD file, while storing the DBPedia resource URI as property. Clearly, any chemical property can be calculated on the fly, or looked up via additional RDF sources, as is done in the previous example. The results are then opened in a JChemPaint-based molecule table functionality in Bioclipse, as shown in Figure 6.

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