An extension of the Plant Ontology project supporting wood anatomy and development research

TitleAn extension of the Plant Ontology project supporting wood anatomy and development research
Publication TypeJournal Article
Year of Publication2012
AuthorsLens F, Cooper L, Gandolfo MA, Groover P, Jaiswal P, Lachenbruch R, Spicer R, Staton D, Stevenson DW, Walls RL, Wegrzyn J
JournalIAWA Journal
Start Page113

A wealth of information on plant anatomy and morphology is available in the current and historical literature, and molecular biologists are producing massive amounts of transcriptome and genome data that can be used to gain better insights into the development, evolution, ecology, and physiological function of plant anatomical attributes. Integrating anatomical and molecular data sets is of major importance to the field of wood science, but this is often hampered by the lack of a standardized, controlled vocabulary that allows for cross-referencing among disparate data types. One approach to overcome this obstacle is through the annotation of data using a common controlled vocabulary or "ontology" (Ashburner et al. 2000; Smith et al. 2007). An ontology is a way of representing knowledge in a given domain that includes a set of terms to describe the classes in that domain, as well as the relationships among terms. Each term can be associated with an array of data such as names, definitions, identification numbers, and genes involved. Ontologies are fundamental for unifying diverse terminologies and are increasingly used by scientists, philosophers, the military and online web search engines. In an ontology, terms are carefully defined, allowing a wide array of researchers to (1) use terms consistently in scientific publications or standardized handbooks on quality/trait evaluations, and (2) search for and integrate data linked to these terms in anatomical, genetic, genomic, and other types of biological databases. The Plant Ontology (PO, is a structured vocabulary and database resource that links plant anatomy and development to gene expression and phenotypic datasets from all areas of plant biology.