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Gemini: memory-efficient integration of hundreds of gene networks with high-order pooling
MOTIVATION: The exponential growth of genomic sequencing data has created ever-expanding repositories of gene networks. Unsupervised network integration methods are critical to learn informative representations for each gene, which are later used as features for downstream applications. However, the...
| Autores principales: | , , , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Oxford University Press
2023
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10311345/ https://www.ncbi.nlm.nih.gov/pubmed/37387142 http://dx.doi.org/10.1093/bioinformatics/btad247 |