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Onto2Vec: joint vector-based representation of biological entities and their ontology-based annotations (1802.00864v1)

Published 31 Jan 2018 in q-bio.QM and cs.AI

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.

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Authors (3)
  1. Fatima Zohra Smaili (2 papers)
  2. Xin Gao (208 papers)
  3. Robert Hoehndorf (27 papers)
Citations (107)

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