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

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

Abstract 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 betwee...

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Bibliographic Details
Main Authors: Xiaoshi Zhong, Rama Kaalia, Jagath C. Rajapakse
Format: Article
Language:English
Published: BMC 2019-12-01
Series:BMC Genomics
Subjects:
Graph embeddings
Vector representations
Gene ontology
CESSM evaluation
Protein-protein interaction prediction
Online Access:http://link.springer.com/article/10.1186/s12864-019-6272-2

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http://link.springer.com/article/10.1186/s12864-019-6272-2

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