GO2Vec : transforming GO terms and proteins to vector representations via graph embeddings

GO2Vec : transforming GO terms and proteins to vector representations via graph embeddings

Background: Semantic similarity between Gene Ontology (GO) terms is a fundamental measure for many bioinformatics applications, such as determining functional similarity between genes or proteins. Most previous research exploited information content to estimate the semantic similarity between GO ter...

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Bibliographic Details
Main Authors: Zhong, Xiaoshi, Kaalia, Rama, Rajapakse, Jagath Chandana
Other Authors: School of Computer Science and Engineering
Format: Journal Article
Language:English
Published: 2021
Subjects:
Science::Biological sciences
Graph Embeddings
Vector Representations
Online Access:https://hdl.handle.net/10356/145882

Internet

https://hdl.handle.net/10356/145882

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