Vector embeddings by sequence similarity and context for improved compression, similarity search, clustering, organization, and manipulation of cDNA libraries

Um, D. H., Knowles, D. A., & Kaiser, G. E. (2025). Vector embeddings by sequence similarity and context for improved compression, similarity search, clustering, organization, and manipulation of cDNA libraries. Computational Biology and Chemistry, 114, 108251. https://doi.org/10.1016/j.compbiolchem.2024.108251
Authors:
Daniel H. Um
David A. Knowles
Gail E. Kaiser
Affiliated Authors:
Daniel H. Um
David A. Knowles
Gail E. Kaiser
Columbia Affiliation:
Author Keywords:
clustering
compression
similarity search
natural language processing
bioinformatics
vector embeddings
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Publication Type:
Article
Unique ID:
10.1016/j.compbiolchem.2024.108251
PMID:
39602973
DOI:
10.1016/j.compbiolchem.2024.108251
Journal:
Computational Biology and Chemistry
Publication Date:
Data Source:
Web of Science
Source Link:
View Web of Science Record

Record Created: