Computing on the anatomical form for disease discovery (338.1)

Abstract

Elucidating evolutionary processes, disease, and developmental dysfunction requires understanding variation in phenotype. However, anatomical information, integration, and retrieval are key challenges as reference to anatomy is largely unstructured or encoded in a variety of formats. An ontology is useful to annotate, link, and retrieve anatomical data, and can be computed on using a reasoner. The use of anatomy ontologies provides a new mechanism on which to base a systems biology approach to understanding phenotypic diversity and dysmorphology. Here, we present our efforts as part of the Monarch Initiative to support the identification of relevant genes linked to human diseases. Towards this end, we constructed the Uberon multi‐species anatomy ontology to provide generalization and links between anatomical structures in model organisms. Use of Uberon with other modular ontologies, such as the Biological Spatial Ontology (BSPO) to record spatial and topological relationships among biological structures, and the Phenotype and Trait Ontology (PATO), enables standardized representation of variation in morphological form. These ontologies act not only as data standards, but provide the connection of anatomical form to gene expression data, atlases, and phenotypic outcomes ‐ thereby enabling deep anatomical analysis to persevere, grow, and shed new light on how biological systems function.