Abstract

Mouse anatomy ontologies provide standard nomenclature for describing normal and mutant mouse anatomy, and are essential for the description and integration of data directly related to anatomy such as gene expression patterns. Building on our previous work on anatomical ontologies for the embryonic and adult mouse, we have recently developed a new and substantially revised anatomical ontology covering all life stages of the mouse. Anatomical terms are organized in complex hierarchies enabling multiple relationships between terms. Tissue classification as well as partonomic, developmental, and other types of relationships can be represented. Hierarchies for specific developmental stages can also be derived. The ontology forms the core of the eMouse Atlas Project (EMAP) and is used extensively for annotating and integrating gene expression patterns and other data by the Gene Expression Database (GXD), the eMouse Atlas of Gene Expression (EMAGE) and other database resources. Here we illustrate the evolution of the developmental and adult mouse anatomical ontologies toward one combined system. We report on recent ontology enhancements, describe the current status, and discuss future plans for mouse anatomy ontology development and application in integrating data resources.

Highlights

  • Anatomy is an integral component for many types of biological data, including gene expression patterns, mutant and disease phenotypes, and normal and pathological processes

  • The ontology forms the core of the eMouse Atlas Project (EMAP) and is used extensively for annotating and integrating gene expression patterns and other data by the Gene Expression Database (GXD), the eMouse Atlas of Gene Expression (EMAGE) and other database resources

  • We report on recent ontology enhancements, describe the current status, and discuss future plans for mouse anatomy ontology development and application in integrating data resources

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Summary

Introduction

Anatomy is an integral component for many types of biological data, including gene expression patterns, mutant and disease phenotypes, and normal and pathological processes. In order to address these and other ontological issues, a non-timed ‘‘abstract’’ representation of the mouse anatomy, referred to as EMAPA, has been developed in which an anatomical structure is represented as a single-unique term. Tree Views for both EMAPA and EMAPS versions of the ontology provide access to associated gene expression data in GXD (see below).

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