Explainable/interpretable artificial intelligence and knowledge graph neural network for synthetic lethality prediction: overview, challenges, and future directions
Salsabil Felloussi, Fatima El Haoussi, Hamid Tairi, Noura Aherrahrou · 2026
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Description
Salsabil Felloussi and co-authors review computer methods for a cancer drug strategy in a 2026 paper. The strategy finds gene pairs that kill cancer cells only when both are blocked at once. Healthy cells survive because they keep one working copy. Testing all pairs in the lab is far too slow and costly, so computer models do the search.
Graph based networks lead the field, learning from maps of gene and protein links. The review sorts how those networks blend gene, protein, and health data layers. It also weighs how well models can explain their picks, a need for clinical trust. New language based tools may add broad medical knowledge to the search.
Catalog record
| CREATOR | Salsabil Felloussi, Fatima El Haoussi, Hamid Tairi, Noura Aherrahrou |
|---|---|
| YEAR | 2026 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 91 KB |
| VERSION | 1.0 |
| LICENSE | CC BY 4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |