English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

The Gene Ontology (GO) has a large and growing number of terms that constitute its vocabulary. An entropy-based ap-proach is presented to automate the characterization of the compositional semantics of GO terms. The motivation is to extend the machine-readability of GO and to offer insights for the continued maintenance and growth of GO. A proto-type implementation illustrates the benefits of the approach. 1 INTRODUCTION The underlying motivation of the work described in this paper is to map annotations based on the Gene Ontology (GO) (Ashburner, et al., 2000) to a semantic representation that exposes the internal semantics of GO terms to computer programs. The Gene Ontology (GO) views each gene prod-uct as being a structural component of a biological entity, being involved in a biological process, and as having a mo-lecular function. These three dimensions of component (C), process (P) and function (F) are hierarchically refined into several thousand subconcepts or GO terms for a fine-grained description of gene products, and ultimately a repre-sentation of collective biological knowledge. The machine-readability of GO is based on explicit IS-A or PART-OF relations between different GO terms (Fig. 1). The represen-tation of each GO term in terms of a phrase in English is primarily meant for human readability, and not machine-readability (Wroe, et al., 2003) (Fig. 1). For example, while both humans and computer programs can understand that ‘Folic Acid Transporter Activity’ is one kind of ‘Vitamin Transporter Activity,” only a human reader can appreciate that proteins annotated with ‘Folic Acid Transporter Activ-ity’ actually

GO-WORDS: An Entropic Approach to Semantic Decomposition of Gene Ontology Terms