Phenotypic similarity. (a) For the GO, the similarity between two concepts can be evaluated based on the relationship between the sets of terms from the ontology that represent those concepts. This relationship can be quantified using metrics such as Jaccard similarity (shown). (b) Natural language processing technique such as sentence embedding using machine learning models or presence and absence of individual words can be used to produce high-dimensional vector representations of concepts, where their position within the vector space allows for quantification of similarity. The example shown plots concepts within three dimensions. (c) Example phenotypic similarity network where nodes represent genes and any associated phenotypic text descriptions. (d) Example phenotypic similarity networks where nodes represent words or phrases drawn from a set of descriptions about some population of plants.