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...

Ful tanımlama

Detaylı Bibliyografya
Asıl Yazarlar: Zhong, Xiaoshi, Kaalia, Rama, Rajapakse, Jagath Chandana
Diğer Yazarlar: School of Computer Science and Engineering
Materyal Türü: Journal Article
Dil:English
Baskı/Yayın Bilgisi: 2021
Konular:
Science::Biological sciences
Graph Embeddings
Vector Representations
Online Erişim:https://hdl.handle.net/10356/145882

Internet

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

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