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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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Related in: MedlinePlus

ODIN interactions panel. Example of interactions delivered by OntoGene as shown by ODIN. The confidence value for each candidate interaction is shown on the left. The two actors in the interactions are provided with their unique identifier, type, and reference name. The columns on the right allow the user to inspect and validate each candidate interaction.
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Figure 3: ODIN interactions panel. Example of interactions delivered by OntoGene as shown by ODIN. The confidence value for each candidate interaction is shown on the left. The two actors in the interactions are provided with their unique identifier, type, and reference name. The columns on the right allow the user to inspect and validate each candidate interaction.

Mentions: The OntoGene pipeline identifies all relevant entities mentioned in the paper, and their interactions, and reports them back to the user as a ranked list (see Figure 3), where the ranking criteria is the system's own confidence for the specific result. The confidence value is computed taking into account several factors, including the relative frequency of the term in the article, its general frequency in PubMed, the context in which the term is mentioned, and the syntactic configuration between two interacting entities (for relationships). A detailed description of the factors that contribute to the computation of the confidence score can be found in [31].


OntoGene web services for biomedical text mining.

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

ODIN interactions panel. Example of interactions delivered by OntoGene as shown by ODIN. The confidence value for each candidate interaction is shown on the left. The two actors in the interactions are provided with their unique identifier, type, and reference name. The columns on the right allow the user to inspect and validate each candidate interaction.
© Copyright Policy - open-access
Related In: Results  -  Collection

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

Figure 3: ODIN interactions panel. Example of interactions delivered by OntoGene as shown by ODIN. The confidence value for each candidate interaction is shown on the left. The two actors in the interactions are provided with their unique identifier, type, and reference name. The columns on the right allow the user to inspect and validate each candidate interaction.
Mentions: The OntoGene pipeline identifies all relevant entities mentioned in the paper, and their interactions, and reports them back to the user as a ranked list (see Figure 3), where the ranking criteria is the system's own confidence for the specific result. The confidence value is computed taking into account several factors, including the relative frequency of the term in the article, its general frequency in PubMed, the context in which the term is mentioned, and the syntactic configuration between two interacting entities (for relationships). A detailed description of the factors that contribute to the computation of the confidence score can be found in [31].

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
Related in: MedlinePlus