AIMC Topic: Biological Ontologies

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RDmap: a map for exploring rare diseases.

Orphanet journal of rare diseases
BACKGROUND: The complexity of the phenotypic characteristics and molecular bases of many rare human genetic diseases makes the diagnosis of such diseases a challenge for clinicians. A map for visualizing, locating and navigating rare diseases based o...

Comparative study using inverse ontology cogency and alternatives for concept recognition in the annotated National Library of Medicine database.

Neural networks : the official journal of the International Neural Network Society
This paper introduces inverse ontology cogency, a concept recognition process and distance function that is biologically-inspired and competitive with alternative methods. The paper introduces inverse ontology cogency as a new alternative method. It ...

An Ontology-Independent Representation Learning for Similar Disease Detection Based on Multi-Layer Similarity Network.

IEEE/ACM transactions on computational biology and bioinformatics
To identify similar diseases has significant implications for revealing the etiology and pathogenesis of diseases and further research in the domain of biomedicine. Currently, most methods for the measurement of disease similarity utilize either asso...

Ontological representation, classification and data-driven computing of phenotypes.

Journal of biomedical semantics
BACKGROUND: The successful determination and analysis of phenotypes plays a key role in the diagnostic process, the evaluation of risk factors and the recruitment of participants for clinical and epidemiological studies. The development of computable...

Outlier concepts auditing methodology for a large family of biomedical ontologies.

BMC medical informatics and decision making
BACKGROUND: Summarization networks are compact summaries of ontologies. The "Big Picture" view offered by summarization networks enables to identify sets of concepts that are more likely to have errors than control concepts. For ontologies that have ...

Towards semantic interoperability: finding and repairing hidden contradictions in biomedical ontologies.

BMC medical informatics and decision making
BACKGROUND: Ontologies are widely used throughout the biomedical domain. These ontologies formally represent the classes and relations assumed to exist within a domain. As scientific domains are deeply interlinked, so too are their representations. W...

Analysis of readability and structural accuracy in SNOMED CT.

BMC medical informatics and decision making
BACKGROUND: The increasing adoption of ontologies in biomedical research and the growing number of ontologies available have made it necessary to assure the quality of these resources. Most of the well-established ontologies, such as the Gene Ontolog...

Web-based interactive mapping from data dictionaries to ontologies, with an application to cancer registry.

BMC medical informatics and decision making
BACKGROUND: The Kentucky Cancer Registry (KCR) is a central cancer registry for the state of Kentucky that receives data about incident cancer cases from all healthcare facilities in the state within 6 months of diagnosis. Similar to all other U.S. a...

Quality assurance and enrichment of biological and biomedical ontologies and terminologies.

BMC medical informatics and decision making
Biological and biomedical ontologies and terminologies are used to organize and store various domain-specific knowledge to provide standardization of terminology usage and to improve interoperability. The growing number of such ontologies and termino...