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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).HiCoEx
A supervised learning model based on Graph Neural Network to predict gene co-expression from chromatin contactsSL_benchmark
Benchmarking study of machine learning methods for prediction of synthetic lethalityTMELand
A software tool for modeling and visualization of Waddington's epigenetic landscape based on dynamical models of gene regulatory network (GRN).KR4SL
SynLethDB
SynLethDB is a comprehensive database (and knowledgebase) for synthetic lethality, a promising strategy of cancer therapeutics and drug discoveryNSF4SL
NSF4SL is a negative-sample-free model for prediction of synthetic lethality (SL) based on a self-supervised contrastive learning framework.PIKE-R2P
LukePi
MGE4SL
In this project, we developed a Multi-Graph Ensemble (MGE) framework combining graph neural network and existing knowledge about genes to predict synthetic lethal (SL) gene pairs.MiT4SL
MiT4SL is the first machine learning model for cross cell line prediction of synthetic lethal (SL) gene pairs. It uses a novel method of triplet representation learning to encode cell line information by integrating multi-omics data of gene expression, PPI network and protein sequences, etc.Love Open Source and this site? Check out how you can help us