aedera/anc2vec
Unsupervised neural network for learning embeddings of GO terms.
This tool helps biologists and computational scientists analyze complex relationships within the Gene Ontology (GO). It takes GO terms and their hierarchical structure as input and produces numerical representations called embeddings. These embeddings can then be used to calculate how semantically similar different GO terms are.
No commits in the last 6 months.
Use this if you need to quantitatively measure the relatedness of Gene Ontology terms for tasks like protein function prediction or gene set enrichment analysis.
Not ideal if your research doesn't involve Gene Ontology terms or if you need to embed other types of biological data.
Stars
21
Forks
10
Language
Python
License
MIT
Category
Last pushed
Feb 19, 2022
Commits (30d)
0
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/embeddings/aedera/anc2vec"
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