English

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

Quantitative Methods 2018-07-13 v1 Artificial Intelligence

Abstract

We propose the Onto2Vec method, an approach to learn feature vectors for biological entities based on their annotations to biomedical ontologies. Our method can be applied to a wide range of bioinformatics research problems such as similarity-based prediction of interactions between proteins, classification of interaction types using supervised learning, or clustering.

Keywords

Cite

@article{arxiv.1802.00864,
  title  = {Onto2Vec: joint vector-based representation of biological entities and their ontology-based annotations},
  author = {Fatima Zohra Smaili and Xin Gao and Robert Hoehndorf},
  journal= {arXiv preprint arXiv:1802.00864},
  year   = {2018}
}
R2 v1 2026-06-23T00:09:19.926Z