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OntoGene web services for biomedical text mining.

Rinaldi F, Clematide S, Marques H, Ellendorff T, Romacker M, Rodriguez-Esteban R - BMC Bioinformatics (2014)

Bottom Line: Traditional architectures, based on monolithic applications, do not offer sufficient flexibility for a wide range of use case scenarios, and therefore open architectures, as provided by web services, are attracting increased interest.We present an approach towards providing advanced text mining capabilities through web services, using a recently proposed standard for textual data interchange (BioC).The web services leverage a state-of-the-art platform for text mining (OntoGene) which has been tested in several community-organized evaluation challenges,with top ranked results in several of them.

View Article: PubMed Central - HTML - PubMed

ABSTRACT
Text mining services are rapidly becoming a crucial component of various knowledge management pipelines, for example in the process of database curation, or for exploration and enrichment of biomedical data within the pharmaceutical industry. Traditional architectures, based on monolithic applications, do not offer sufficient flexibility for a wide range of use case scenarios, and therefore open architectures, as provided by web services, are attracting increased interest. We present an approach towards providing advanced text mining capabilities through web services, using a recently proposed standard for textual data interchange (BioC). The web services leverage a state-of-the-art platform for text mining (OntoGene) which has been tested in several community-organized evaluation challenges,with top ranked results in several of them.

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Example of output of the OG text mining service in BioC format. The output of the system is generated in the the BioC specification format. This output was generated by querying for chemicals and diseases on PubMed abstract 20130422. Colors added for clarity. Offsets of annotated terms can be obtained with a separate query.
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Figure 2: Example of output of the OG text mining service in BioC format. The output of the system is generated in the the BioC specification format. This output was generated by querying for chemicals and diseases on PubMed abstract 20130422. Colors added for clarity. Offsets of annotated terms can be obtained with a separate query.

Mentions: The OntoGene web services have been implemented using the RESTful approach [51]. They accept simple XML files as input, based on the BioC specification. The output of the system is generated in the same format. For example, a query aiming at retrieving chemicals and diseases from PubMed abstract 20130422 would generate the output shown in Figure 2.


OntoGene web services for biomedical text mining.

Rinaldi F, Clematide S, Marques H, Ellendorff T, Romacker M, Rodriguez-Esteban R - BMC Bioinformatics (2014)

Example of output of the OG text mining service in BioC format. The output of the system is generated in the the BioC specification format. This output was generated by querying for chemicals and diseases on PubMed abstract 20130422. Colors added for clarity. Offsets of annotated terms can be obtained with a separate query.
© Copyright Policy - open-access
Related In: Results  -  Collection

License 1 - License 2
Show All Figures
getmorefigures.php?uid=PMC4255746&req=5

Figure 2: Example of output of the OG text mining service in BioC format. The output of the system is generated in the the BioC specification format. This output was generated by querying for chemicals and diseases on PubMed abstract 20130422. Colors added for clarity. Offsets of annotated terms can be obtained with a separate query.
Mentions: The OntoGene web services have been implemented using the RESTful approach [51]. They accept simple XML files as input, based on the BioC specification. The output of the system is generated in the same format. For example, a query aiming at retrieving chemicals and diseases from PubMed abstract 20130422 would generate the output shown in Figure 2.

Bottom Line: Traditional architectures, based on monolithic applications, do not offer sufficient flexibility for a wide range of use case scenarios, and therefore open architectures, as provided by web services, are attracting increased interest.We present an approach towards providing advanced text mining capabilities through web services, using a recently proposed standard for textual data interchange (BioC).The web services leverage a state-of-the-art platform for text mining (OntoGene) which has been tested in several community-organized evaluation challenges,with top ranked results in several of them.

View Article: PubMed Central - HTML - PubMed

ABSTRACT
Text mining services are rapidly becoming a crucial component of various knowledge management pipelines, for example in the process of database curation, or for exploration and enrichment of biomedical data within the pharmaceutical industry. Traditional architectures, based on monolithic applications, do not offer sufficient flexibility for a wide range of use case scenarios, and therefore open architectures, as provided by web services, are attracting increased interest. We present an approach towards providing advanced text mining capabilities through web services, using a recently proposed standard for textual data interchange (BioC). The web services leverage a state-of-the-art platform for text mining (OntoGene) which has been tested in several community-organized evaluation challenges,with top ranked results in several of them.

Show MeSH