Uberon: towards a comprehensive multi-species anatomy ontology

The lack of a single unified species-neutral ontology covering the anatomy of a variety of metazoans is a hindrance to translating model organism research to human health. We have developed an Uber-anatomy ontology to fill this need, filling the gap between the CARO upper-level ontology and species-specific anatomical ontologies

FAIR principles and the IEDB: short-term improvements and a long-term vision of OBO-foundry mediated machine-actionable interoperability.

The Immune Epitope Database (IEDB), at www.iedb.org, has the mission to make published experimental data relating to the recognition of immune epitopes easily available to the scientific public. By presenting curated data in a searchable database, we have liberated it from the tables and figures of journal articles, making it more accessible and usable by immunologists. Recently, the principles of Findability, Accessibility, Interoperability and Reusability have been formulated as goals that data repositories should meet to enhance the usefulness of their data holdings. We here examine how the IEDB complies with these principles and identify broad areas of success, but also areas for improvement. We describe short-term improvements to the IEDB that are being implemented now, as well as a long-term vision of true 'machine-actionable interoperability', which we believe will require community agreement on standardization of knowledge representation that can be built on top of the shared use of ontologies

The NCBO OBOF to OWL Mapping

Two of the most significant formats for biomedical ontologies are the Open Biomedical Ontologies Format (OBOF) and the Web Ontology Language (OWL). To make it possible to translate ontologies between these two representation formats, the National Center for Biomedical Ontology (NCBO) has developed a mapping between the OBOF and OWL formats as well as inter-conversion software. The goal was to allow the sharing of tools, ontologies, and associated data between the OBOF and Semantic Web communities.

OBOF does not have a formal grammar, so the NCBO had to capture its intended semantics to map it to OWL.

This official NCBO mapping was used to make all OBO Foundry ontologies available in OWL. 

Availability: This mapping functionality can be embedded into OBO-Edit and Protégé-OWL ontology editors. This software is available at: http://bioontology.org/wiki/index.php/OboInOwl:Main_Pag

The Plant Ontology: A common reference ontology for plants

The Plant Ontology (PO) (http://www.plantontology.org) (Jaiswal et al., 2005; Avraham et al., 2008) was designed to facilitate cross-database querying and to foster consistent use of plant-specific terminology in annotation. As new data are generated from the ever-expanding list of plant genome projects, the need for a consistent, cross-taxon vocabulary has grown. To meet this need, the PO is being expanded to represent all plants. This is the first ontology designed to encompass anatomical structures as well as growth and developmental stages across such a broad taxonomic range. While other ontologies such as the Gene Ontology (GO) (The Gene Ontology Consortium, 2010) or Cell Type Ontology (CL) (Bard et al., 2005) cover all living organisms, they are confined to structures at the cellular level and below. The diversity of growth forms and life histories within plants presents a challenge, but also provides unique opportunities to study developmental and evolutionary homology across organisms

Modularization for the Cell Ontology

One of the premises of the OBO Foundry is that development of an orthogonal set of ontologies will increase domain expert contributions and logical interoperability, and decrease maintenance workload. For these reasons, the Cell Ontology (CL) is being re-engineered. This process requires the extraction of sub-modules from existing OBO ontologies, which presents a number of practical engineering challenges. These extracted modules may be intended to cover a narrow or a broad set of species. In addition, applications and resources that make use of the Cell Ontology have particular modularization requirements, such as the ability to extract custom subsets or unions of the Cell Ontology with other OBO ontologies. These extracted modules may be intended to cover a narrow or a broad set of species, which presents unique complications.

We discuss some of these requirements, and present our progress towards a customizable simple-to-use modularization tool that leverages existing OWL-based tools and opens up their use for the CL and other ontologies

Cross-Product Extensions of the Gene Ontology

The Gene Ontology is being normalized and extended to include computable logical definitions. These definitions are partitioned into mutually exclusive cross-product sets, many of which reference other OBO Foundry ontologies. The results can be used to reason over the ontology, and to make cross-ontology queries

Atmospheric conditions and their effect on ball-milled magnesium diboride

Magnesium diboride bulk pellets were fabricated from pre-reacted MgB2 powder ball milled with different amounts of exposure to air. Evidence of increased electron scattering including increased resistivity, depressed Tc, and enhanced Hc2 of the milled and heat treated samples were observed as a result of increased contact with air. These and other data were consistent with alloying with carbon as a result of exposure to air. A less clear trend of decreased connectivity associated with air exposure was also observed. In making the case that exposure to air should be considered a doping process, these results may explain the wide varibability of "undoped" MgB2 properties extant in the literature.Comment: Work presented at ASC 2006 in Seattl

National Center for Biomedical Ontology: Advancing biomedicine through structured organization of scientific knowledge

The National Center for Biomedical Ontology is a consortium that comprises leading informaticians, biologists, clinicians, and ontologists, funded by the National Institutes of Health (NIH) Roadmap, to develop innovative technology and methods that allow scientists to record, manage, and disseminate biomedical information and knowledge in machine-processable form. The goals of the Center are (1) to help unify the divergent and isolated efforts in ontology development by promoting high quality open-source, standards-based tools to create, manage, and use ontologies, (2) to create new software tools so that scientists can use ontologies to annotate and analyze biomedical data, (3) to provide a national resource for the ongoing evaluation, integration, and evolution of biomedical ontologies and associated tools and theories in the context of driving biomedical projects (DBPs), and (4) to disseminate the tools and resources of the Center and to identify, evaluate, and communicate best practices of ontology development to the biomedical community. Through the research activities within the Center, collaborations with the DBPs, and interactions with the biomedical community, our goal is to help scientists to work more effectively in the e-science paradigm, enhancing experiment design, experiment execution, data analysis, information synthesis, hypothesis generation and testing, and understand human disease

Uberon, an integrative multi-species anatomy ontology

We present Uberon, an integrated cross-species ontology consisting of over 6,500 classes representing a variety of anatomical entities, organized according to traditional anatomical classification criteria. The ontology represents structures in a species-neutral way and includes extensive associations to existing species-centric anatomical ontologies, allowing integration of model organism and human data. Uberon provides a necessary bridge between anatomical structures in different taxa for cross-species inference. It uses novel methods for representing taxonomic variation, and has proved to be essential for translational phenotype analyses. Uberon is available at http://uberon.or

Detecting morphed passport photos : a training and individual differences approach

Our reliance on face photos for identity verification is at odds with extensive research which shows that matching pairs of unfamiliar faces is highly prone to error. This process can therefore be exploited by identity fraudsters seeking to deceive ID checkers (e.g. using a stolen passport which contains an image of similar looking individual to deceive border control officials). In this study we build on previous work which sought to quantify the threat posed by a relatively new type of fraud - morphed passport photos. Participants were initially unaware of the presence of morphs in a series of face photo arrays, and were simply asked to detect which images they thought had been digitally manipulated (i.e. “images that didn’t look quite right”). All participants then received basic information on morph fraud and rudimentary guidance on how to detect such images, followed by a morph detection training task (Training Group, N = 40), or a non-face control task (Guidance Group, N = 40). Participants also completed a post-guidance/training morph detection task, and the Models Face Matching Test (MFMT). Our findings show that baseline morph detection rates were poor, that morph detection training significantly improved the identification of these images over and above basic guidance, and accuracy on the mismatch condition of the MFMT correlated with morph detection ability. The results are discussed in relation to potential counter-measures for morph-based identity fraud