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Found 4 papers, 1 papers with code
Graph Representation Learning on Tissue-Specific Multi-Omics
Overall, the combination of RNA-sequencing and gene methylation data leads to a link prediction accuracy of 71% on GGI networks.
Is Disentanglement all you need? Comparing Concept-based & Disentanglement Approaches
Concept-based explanations have emerged as a popular way of extracting human-interpretable representations from deep discriminative models.
Using ontology embeddings for structural inductive bias in gene expression data analysis
Stratifying cancer patients based on their gene expression levels allows improving diagnosis, survival analysis and treatment planning.
Incorporating network based protein complex discovery into automated model construction
We propose a method for gene expression based analysis of cancer phenotypes incorporating network biology knowledge through unsupervised construction of computational graphs.
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