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 potentialUnveiling fine-scale spatial structures and amplifying gene expression signals in ultra-large ST slices with HERGAST
Gong Y, Yuan X, Jiao Q, Yu Z. Unveiling fine-scale spatial structures and amplifying gene expression signals in ultra-large ST slices with HERGAST. Nature Communications 2025, 16: 3977. PMID: 40295488, PMCID: PMC12037780, DOI: 10.1038/s41467-025-59139-w.Peer-Reviewed Original ResearchConceptsGene expression signalsSpatial transcriptomics data analysisExpression signalsTranscriptome data analysisHeterogeneous graph networkReal-world datasetsSpatial expression patternsOver-smoothing problemSpatial transcriptomics dataGlobal spatial relationshipsST data analysisTranscriptome dataUltra-large-scaleConquer strategyExpression patternsGraph networkData splittingGenes
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