Predicting Gene-Disease Associations with Knowledge Graph Embeddings over Multiple Ontologies

05/11/2021
by   Susana Nunes, et al.
0

Ontology-based approaches for predicting gene-disease associations include the more classical semantic similarity methods and more recently knowledge graph embeddings. While semantic similarity is typically restricted to hierarchical relations within the ontology, knowledge graph embeddings consider their full breadth. However, embeddings are produced over a single graph and complex tasks such as gene-disease association may require additional ontologies. We investigate the impact of employing richer semantic representations that are based on more than one ontology, able to represent both genes and diseases and consider multiple kinds of relations within the ontologies. Our experiments demonstrate the value of employing knowledge graph embeddings based on random-walks and highlight the need for a closer integration of different ontologies.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
04/29/2018

OPA2Vec: combining formal and informal content of biomedical ontologies to improve similarity-based prediction

Motivation: Ontologies are widely used in biology for data annotation, i...
research
10/20/2021

Why Settle for Just One? Extending EL++ Ontology Embeddings with Many-to-Many Relationships

Knowledge Graph (KG) embeddings provide a low-dimensional representation...
research
11/13/2019

Predicting microRNA-disease associations from knowledge graph using tensor decomposition with relational constraints

Motivation: MiRNAs are a kind of small non-coding RNAs that are not tran...
research
12/18/2019

Semantic integration of disease-specific knowledge

Biomedical researchers working on a specific disease need up-to-date and...
research
05/18/2023

The Water Health Open Knowledge Graph

Recently, an increasing interest in the management of water and health r...
research
06/05/2022

A knowledge graph representation learning approach to predict novel kinase-substrate interactions

The human proteome contains a vast network of interacting kinases and su...
research
03/29/2023

From axioms over graphs to vectors, and back again: evaluating the properties of graph-based ontology embeddings

Several approaches have been developed that generate embeddings for Desc...

Please sign up or login with your details

Forgot password? Click here to reset