2024
Expression and prognostic value of cell‐cycle‐associated genes in lung squamous cell carcinoma
Xu X, Jin K, Xu X, Yang Y, Zhou B. Expression and prognostic value of cell‐cycle‐associated genes in lung squamous cell carcinoma. The Journal Of Gene Medicine 2024, 26: e3735. PMID: 39171952, DOI: 10.1002/jgm.3735.Peer-Reviewed Original ResearchConceptsCell cycle-associated genesLung squamous carcinomaCell cycleMRNA expression dataGene expression profilesAssociated with positive prognosisCause of cancer-related deathExpression dataCancer Genome AtlasExpressed genesSquamous cell carcinomaLung squamous cell carcinomaTargeted therapy trialsGroup of patientsCancer-related deathsExpression of CDK4GenesExpression trendsExpression profilesMolecular studiesGenome AtlasSquamous carcinomaCell carcinomaPathological stagePrognostic valueCGMega: explainable graph neural network framework with attention mechanisms for cancer gene module dissection
Li H, Han Z, Sun Y, Wang F, Hu P, Gao Y, Bai X, Peng S, Ren C, Xu X, Liu Z, Chen H, Yang Y, Bo X. CGMega: explainable graph neural network framework with attention mechanisms for cancer gene module dissection. Nature Communications 2024, 15: 5997. PMID: 39013885, PMCID: PMC11252405, DOI: 10.1038/s41467-024-50426-6.Peer-Reviewed Original ResearchDecoding protein binding landscape on circular RNAs with base-resolution transformer models
Wu H, Liu X, Fang Y, Yang Y, Huang Y, Pan X, Shen H. Decoding protein binding landscape on circular RNAs with base-resolution transformer models. Computers In Biology And Medicine 2024, 171: 108175. PMID: 38402841, DOI: 10.1016/j.compbiomed.2024.108175.Peer-Reviewed Original ResearchConceptsRNA-binding protein binding sitesRNA-binding proteinsCircRNA transcriptsBinding sitesBinding to RNA-binding proteinsSingle-nucleotide resolutionCovalent loop structureCircular RNAsBound nucleotideBinding motifBinding landscapeGene expressionTranscriptionRNANucleotideLoop structureCircRNAsProteinEndogenous RNAFragmentsSitesComputational methodsMotifGenesConvolutional neural network
2023
Enhancing Cancer Gene Prediction through Aligned Fusion of Multiple PPI Networks Using Graph Transformer Models
Han Z, Yu G, Yang Y. Enhancing Cancer Gene Prediction through Aligned Fusion of Multiple PPI Networks Using Graph Transformer Models. 2023, 00: 542-547. DOI: 10.1109/bibm58861.2023.10385593.Peer-Reviewed Original ResearchProtein-protein interaction networkProtein-protein interactionsCancer gene predictionCancer genesGene predictionCancer cell line datasetsGene interaction relationshipsCell line datasetsCancer driver genesMulti-omics dataPan-cancer datasetProtein-proteinPPI networkGene associationsGene representationMulti-omicsDriver genesGenesGraph neural networksCancer researchGraph transformer networkState-of-the-art performanceCancerState-of-the-artGraph transformation modelIsoform Function Prediction Based on Heterogeneous Graph Attention Networks
Guo K, Li Y, Chen H, Shen H, Yang Y. Isoform Function Prediction Based on Heterogeneous Graph Attention Networks. 2023, 00: 522-527. DOI: 10.1109/bibm58861.2023.10386048.Peer-Reviewed Original ResearchIsoform function predictionFunction predictionIsoform functionGene OntologyMechanisms of gene regulationFunctions of isoformsProtein language modelsFunctional labelsProtein sequencesGO annotationsGene regulationSequence featuresGO termsMRNA moleculesIsoform levelsGene levelBiological processesGenesIsoformsSpecies datasetInteraction dataIntricate mechanismsProteinHeterogeneous graph attention networkAnnotation