OntoCAT - an integrated programming toolkit for common ontology application tasks

OntoCAT provides high level abstraction for interacting with ontology resources including local ontology files in standard OWL and OBO formats (via OWL API) and public ontology repositories: EBI Ontology Lookup Service (OLS) and NCBO BioPortal. Each resource is wrapped behind easy to learn Java, Bioconductor/R and REST web service commands enabling reuse and integration of ontology software efforts despite variation in technologies

OntoCAT - a simpler way to access ontology resources

OntoCAT is an open source package developed to simplify the task of querying heterogeneous ontology resources. It supports local ontologies in OBO and OWL format as well as public repositories NCBO BioPortal and EBI Ontology Lookup Service (OLS). It is available from "http://ontocat.sourceforge.net":http://ontocat.sourceforge.ne

Anatomy ontologies and potential users: bridging the gap.

MOTIVATION: To evaluate how well current anatomical ontologies fit the way real-world users apply anatomy terms in their data annotations. METHODS: Annotations from three diverse multi-species public-domain datasets provided a set of use cases for matching anatomical terms in two major anatomical ontologies (the Foundational Model of Anatomy and Uberon), using two lexical-matching applications (Zooma and Ontology Mapper). RESULTS: Approximately 1500 terms were identified; Uberon/Zooma mappings provided 286 matches, compared to the control and Ontology Mapper returned 319 matches. For the Foundational Model of Anatomy, Zooma returned 312 matches, and Ontology Mapper returned 397. CONCLUSIONS: Our results indicate that for our datasets the anatomical entities or concepts are embedded in user-generated complex terms, and while lexical mapping works, anatomy ontologies do not provide the majority of terms users supply when annotating data. Provision of searchable cross-products for compositional terms is a key requirement for using ontologies.RIGHTS : This article is licensed under the BioMed Central licence at http://www.biomedcentral.com/about/license which is similar to the 'Creative Commons Attribution Licence'. In brief you may : copy, distribute, and display the work; make derivative works; or make commercial use of the work - under the following conditions: the original author must be given credit; for any reuse or distribution, it must be made clear to others what the license terms of this work are

Modeling sample variables with an Experimental Factor Ontology

Motivation: Describing biological sample variables with ontologies is complex due to the cross-domain nature of experiments. Ontologies provide annotation solutions; however, for cross-domain investigations, multiple ontologies are needed to represent the data. These are subject to rapid change, are often not interoperable and present complexities that are a barrier to biological resource users

OntoCAT -- simple ontology search and integration in Java, R and REST/JavaScript

<p>Abstract</p> <p>Background</p> <p>Ontologies have become an essential asset in the bioinformatics toolbox and a number of ontology access resources are now available, for example, the EBI Ontology Lookup Service (OLS) and the NCBO BioPortal. However, these resources differ substantially in mode, ease of access, and ontology content. This makes it relatively difficult to access each ontology source separately, map their contents to research data, and much of this effort is being replicated across different research groups.</p> <p>Results</p> <p>OntoCAT provides a seamless programming interface to query heterogeneous ontology resources including OLS and BioPortal, as well as user-specified local OWL and OBO files. Each resource is wrapped behind easy to learn Java, Bioconductor/R and REST web service commands enabling reuse and integration of ontology software efforts despite variation in technologies. It is also available as a stand-alone MOLGENIS database and a Google App Engine application.</p> <p>Conclusions</p> <p>OntoCAT provides a robust, configurable solution for accessing ontology terms specified locally and from remote services, is available as a stand-alone tool and has been tested thoroughly in the ArrayExpress, MOLGENIS, EFO and Gen2Phen phenotype use cases.</p> <p>Availability</p> <p><url>http://www.ontocat.org</url></p

The MOLGENIS toolkit: rapid prototyping of biosoftware at the push of a button

Peer reviewe

Screenshot of ClinMiner ontology browser.

<p>Tabs allow to switch between different sources and UMLS (A).<strong> Searching.</strong> Typing a query into the input field (B) brings up a list of suggested search terms. Results are displayed in the middle pane (D). Clicking on any of the terms brings back the hierarchy view shown above. <strong>Browsing.</strong> The currently active term (here <em>Acute bronchitis C0149514</em>) is highlighted in yellow (G) in the middle pane (D) together with its siblings. Parent terms of the active term are displayed in the left pane and child terms are displayed in the right pane (F). Meta data for the active term including semantic types, definitions, non-isa relations to other concepts and co-occurrence information is shown in the vignette directly below (H). A plus sign (+) after term label denotes concepts with children, and number in brackets reflects the number of participants annotated to a particular term (or its children) in the database. Selecting a study from the listbox box (C) switches the data-driven perspective that only shows a fragment of the ontology tree relevant to a particular study. A larger version of the figure is available on fighshare via: http://dx.doi.org/10.6084/m9.figshare.155879</p

SUPPLEMENTARY MATERIAL: Patterns of drug-drug co-occurrence in Electronic Health Records in patients with epilepsy

<p>Supplementary material for the ISMB 2014 submission</p

SUPPLEMENTARY MATERIAL: EHR-based phenome wide association study in pancreatic cancer

<p>Supplementary material for the CRI 2014 submission</p

Developing an application ontology for annotation of experimental variables &#x2013; Experimental Factor Ontology

The Experimental Factor Ontology (&#x22;www.ebi.ac.uk/efo&#x22;:http://www.ebi.ac.uk/efo) is an application focused ontology modelling the experimental factors in ArrayExpress. The ontology has been developed to increase the richness of the annotations that are currently made in the ArrayExpress repository, to promote consistent annotation, to facilitate automatic annotation and to integrate external data. The methodology employed in the development of EFO involves construction of mappings to multiple existing domain specific ontologies, such as the Disease Ontology and Cell Type Ontology