Onto2Vec: joint vector-based representation of biological entities and their ontology-based annotations.

ABSTRACT:

Motivation

Biological knowledge is widely represented in the form of ontology-based annotations: ontologies describe the phenomena assumed to exist within a domain, and the annotations associate a (kind of) biological entity with a set of phenomena within the domain. The structure and information contained in ontologies and their annotations make them valuable for developing machine learning, data analysis and knowledge extraction algorithms; notably, semantic similarity is widely used to identify relations between biological entities, and ontology-based annotations are frequently used as features in machine learning applications.

Results

We propose the Onto2Vec method, an approach to learn feature vectors for biological entities based on their annotations to biomedical onto

SUBMITTER: Smaili FZ 

PROVIDER: S-EPMC6022543 | biostudies-literature | 2018 Jul

REPOSITORIES: biostudies-literature