JieZheng-ShanghaiTech/PiLSL
PiLSL is a pairwise interaction learning-based graph neural network (GNN) model for prediction of synthetic lethality (SL) as anti-cancer drug targets. It learns the representation of pairwise interaction between two genes from a knowledge graph (KG).
This tool helps cancer researchers and drug discovery scientists identify potential synthetic lethal (SL) gene pairs. You provide comprehensive gene relationship data from a knowledge graph and multi-omics features, and it predicts which gene pairs, when both are targeted, could effectively kill cancer cells. This helps identify new drug targets for cancer therapies.
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Use this if you are a cancer researcher or drug discovery scientist looking for novel synthetic lethal gene pairs to develop targeted anti-cancer treatments.
Not ideal if you need a tool for general gene interaction prediction or if you lack detailed biological knowledge graph data for human cancers.
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12
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Language
Python
License
MIT
Category
Last pushed
Dec 04, 2024
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