Gene Interaction Prediction
2 papers with code • 2 benchmarks • 1 datasets
Most implemented papers
GNE: a deep learning framework for gene network inference by aggregating biological information
However, it is still a challenging task to aggregate heterogeneous biological information such as gene expression and gene interactions to achieve more accurate inference for prediction and discovery of new gene interactions.
Communicative Subgraph Representation Learning for Multi-Relational Inductive Drug-Gene Interaction Prediction
To address these problems, we propose a novel Communicative Subgraph representation learning for Multi-relational Inductive drug-Gene interactions prediction (CoSMIG), where the predictions of drug-gene relations are made through subgraph patterns, and thus are naturally inductive for unseen drugs/genes without retraining or utilizing external domain features.