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Semi-automated ontology generation within OBO-Edit.

ABSTRACT: MOTIVATION: Ontologies and taxonomies have proven highly beneficial for biocuration. The Open Biomedical Ontology (OBO) Foundry alone lists over 90 ontologies mainly built with OBO-Edit. Creating and maintaining such ontologies is a labour-intensive, difficult, manual process. Automating parts of it is of great importance for the further development of ontologies and for biocuration. RESULTS: We have developed the Dresden Ontology Generator for Directed Acyclic Graphs (DOG4DAG), a system which supports the creation and extension of OBO ontologies by semi-automatically generating terms, definitions and parent-child relations from text in PubMed, the web and PDF repositories. DOG4DAG is seamlessly integrated into OBO-Edit. It generates terms by identifying statistically significant noun phrases in text. For definitions and parent-child relations it employs pattern-based web searches. We systematically evaluate each generation step using manually validated benchmarks. The term generation leads to high-quality terms also found in manually created ontologies. Up to 78% of definitions are valid and up to 54% of child-ancestor relations can be retrieved. There is no other validated system that achieves comparable results. By combining the prediction of high-quality terms, definitions and parent-child relations with the ontology editor OBO-Edit we contribute a thoroughly validated tool for all OBO ontology engineers. AVAILABILITY: DOG4DAG is available within OBO-Edit 2.1 at http://www.oboedit.org. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

SUBMITTER: Wachter T

PROVIDER: S-EPMC2881373 | biostudies-literature | 2010 Jun

REPOSITORIES: biostudies-literature

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Semi-automated ontology generation within OBO-Edit.

Wächter Thomas T Schroeder Michael M

Bioinformatics (Oxford, England) 20100601 12

<h4>Motivation</h4>Ontologies and taxonomies have proven highly beneficial for biocuration. The Open Biomedical Ontology (OBO) Foundry alone lists over 90 ontologies mainly built with OBO-Edit. Creating and maintaining such ontologies is a labour-intensive, difficult, manual process. Automating parts of it is of great importance for the further development of ontologies and for biocuration.<h4>Results</h4>We have developed the Dresden Ontology Generator for Directed Acyclic Graphs (DOG4DAG), a s ...[more]

PMID: 20529942

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Project description:BackgroundThe haemostatic balance is an equilibrium of pro- and anticoagulant factors that work synergistically to prevent bleeding and thrombosis. As thrombin is the central enzyme in the coagulation pathway, it is desirable to measure thrombin generation (TG) in order to detect possible bleeding or thrombotic phenotypes, as well as to investigate the capacity of drugs affecting the formation of thrombin. By investigating the underlying processes of TG (i.e., prothrombin conversion and inactivation), additional information is collected about the dynamics of thrombin formation.ObjectivesTo obtain reference values for thrombin dynamics (TD) analysis in 112 healthy donors using an automated system for TG.MethodsTG was measured on the ST Genesia, fibrinogen on the Start, anti-thrombin (AT) on the STA R Max and α2Macroglobulin (α2M) with an in-house chromogenic assay.ResultsTG was measured using STG-BleedScreen, STG-ThromboScreen and STG-DrugScreen. The TG data was used as an input for TD analysis, in combination with plasma levels of AT, α2M and fibrinogen that were 113% (108-118%), 2.6 μM (2.2 μM-3.1 μM) and 2.9 g/L (2.6-3.2 g/L), respectively. The maximum rate of the prothrombinase complex (PCmax) and the total amount of prothrombin converted (PCtot) increased with increasing tissue factor (TF) concentration. PCtot increased from 902 to 988 nM, whereas PCmax increased from 172 to 508 nM/min. Thrombin (T)-AT and T-α2M complexes also increased with increasing TF concentration (i.e., from 860 to 955 nM and from 28 to 33 nm, respectively). PCtot, T-AT and T-α2M complex formation were strongly inhibited by addition of thrombomodulin (-44%, -43%, and -48%, respectively), whereas PCmax was affected less (-24%). PCtot, PCmax, T-AT, and T-α2M were higher in women using oral contraceptives (OC) compared to men/women without OC, and inhibition by thrombomodulin was also significantly less in women on OC (p < 0.05).ConclusionsTG measured on the ST Genesia can be used as an input for TD analysis. The data obtained can be used as reference values for future clinical studies as the balance between prothrombin conversion and thrombin inactivation has shown to be useful in several clinical settings.

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Project description:UnlabelledBackgroundClassification of chemical compounds into compound classes by using structure derived descriptors is a well-established method to aid the evaluation and abstraction of compound properties in chemical compound databases. MeSH and recently ChEBI are examples of chemical ontologies that provide a hierarchical classification of compounds into general compound classes of biological interest based on their structural as well as property or use features. In these ontologies, compounds have been assigned manually to their respective classes. However, with the ever increasing possibilities to extract new compounds from text documents using name-to-structure tools and considering the large number of compounds deposited in databases, automated and comprehensive chemical classification methods are needed to avoid the error prone and time consuming manual classification of compounds.ResultsIn the present work we implement principles and methods to construct a chemical ontology of classes that shall support the automated, high-quality compound classification in chemical databases or text documents. While SMARTS expressions have already been used to define chemical structure class concepts, in the present work we have extended the expressive power of such class definitions by expanding their structure-based reasoning logic. Thus, to achieve the required precision and granularity of chemical class definitions, sets of SMARTS class definitions are connected by OR and NOT logical operators. In addition, AND logic has been implemented to allow the concomitant use of flexible atom lists and stereochemistry definitions. The resulting chemical ontology is a multi-hierarchical taxonomy of concept nodes connected by directed, transitive relationships.ConclusionsA proposal for a rule based definition of chemical classes has been made that allows to define chemical compound classes more precisely than before. The proposed structure-based reasoning logic allows to translate chemistry expert knowledge into a computer interpretable form, preventing erroneous compound assignments and allowing automatic compound classification. The automated assignment of compounds in databases, compound structure files or text documents to their related ontology classes is possible through the integration with a chemical structure search engine. As an application example, the annotation of chemical structure files with a prototypic ontology is demonstrated.

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Semi-automated ontology generation within OBO-Edit.

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Semi-automated ontology generation within OBO-Edit.

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