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Found 4 papers, 1 papers with code
Biological Random Walks: multi-omics integration for disease gene prioritization
Motivation: Over the past decade, network-based approaches have proven useful in identifying disease modules within the human interactome, often providing insights into key mechanisms and guiding the quest for therapeutic targets.
Network Based Approach to Gene Prioritization at Genome-Wide Association Study Loci
Results: We present the Relations-Maximization Method, a dense module searching method to identify putative causal genes at GWAS loci through the generation of candidate sub-networks derived by integrating association signals from GWAS data into the gene co-regulation network.
Network and Sequence-Based Prediction of Protein-Protein Interactions
Background:Typically, proteins perform key biological functions by interacting with each other.
Biological Random Walks: integrating heterogeneous data in disease gene prioritization
This work proposes a unified framework to leverage biological information in network propagation-based gene prioritization algorithms.
