Genome-scale prediction of context-specific synthetic lethality beyond protein interaction networks

Abstract excerpt

Identifying synthetic lethal (SL) interactions offers a principled framework for discovering disease-specific therapeutic targets. However, current machine learning approaches heavily rely on curated protein-protein interaction networks. Because these networks cover only ∼7,500 proteins, they severely restrict the search space of human gene pairs and introduce systematic biases toward well-characterized genes. To...

Topics

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• Artificial Intelligence
• Bioinformatics and Genomic Networks
• Computer Simulation
• Deep Learning
• Drug Evaluation, Preclinical
• Mutation
• Neoplasms
• Synthetic Lethal Mutations

Identifiers and source

Literature Corpus work

563cd263-0467-5f7d-bee0-00a69cf8c1fc

DOI

10.64898/2026.07.31.742101