2025
ProDualNet: dual-target protein sequence design method based on protein language model and structure model
Cheng L, Wei T, Cui X, Chen H, Yu Z. ProDualNet: dual-target protein sequence design method based on protein language model and structure model. Briefings In Bioinformatics 2025, 26: bbaf391. PMID: 40856523, PMCID: PMC12378908, DOI: 10.1093/bib/bbaf391.Peer-Reviewed Original ResearchConceptsSequence-structure informationProtein language modelsAllosteric bindingIn silico evaluationSequence design methodProtein sequencesProtein designBinding proteinBiological processesMulti-target strategyProteinHeterogeneous graph networkMultiple receptorsMultiple test setsLanguage modelGraph networkBindingExperimental structuresSingle receptorDesign networksReceptorsTest setTherapeutic potential
2024
DeepAEG: a model for predicting cancer drug response based on data enhancement and edge-collaborative update strategies
Lao C, Zheng P, Chen H, Liu Q, An F, Li Z. DeepAEG: a model for predicting cancer drug response based on data enhancement and edge-collaborative update strategies. BMC Bioinformatics 2024, 25: 105. PMID: 38461284, PMCID: PMC10925015, DOI: 10.1186/s12859-024-05723-8.Peer-Reviewed Original ResearchConceptsHigh-dimensional representationsCancer drug responseEnd-to-end deep learning modelGraph convolutional networkEnd-to-endDeep learning modelsHybrid graph convolutional networkDrug responseMultiple test setsConvolutional networkFeature extractionUpdate mechanismUpdate strategyData enhancementUpdate modeMultiple evaluation parametersLearning modelsTest setGenome integritySequence recombinationGenomic characteristicsPrediction accuracyTopological structurePersonalized cancer therapyEffective clinical treatment options
This site is protected by hCaptcha and its Privacy Policy and Terms of Service apply