2025
SuperGLUE facilitates an explainable training framework for multi-modal data analysis
Liu T, Zhao J, Zhao H. SuperGLUE facilitates an explainable training framework for multi-modal data analysis. Cell Reports Methods 2025, 5: 101167. PMID: 40914154, DOI: 10.1016/j.crmeth.2025.101167.Peer-Reviewed Original ResearchConceptsData integrationProbabilistic deep learningMulti-modal data analysisInference of gene regulatory networksMulti-modal data integrationDeep learningGene regulatory networksTraining frameworkBaseline modelRegulatory networksComplex biological systemsRegulatory relationshipsSensing dataCell statesGlobal structureArea of active researchActive researchOmicsBiological featuresScalable methodFrameworkBiological systemsStatistical modelNetworkBiological linkages
2013
Application of Bayesian Sparse Factor Analysis Models in Bioinformatics
Ma H, Zhao H. Application of Bayesian Sparse Factor Analysis Models in Bioinformatics. 2013, 350-365. DOI: 10.1017/cbo9781139226448.018.Peer-Reviewed Original ResearchFactor analysis modelClassical factor analysis modelLatent variable modelStatistical methodsInferential methodsVariable modelComputational biologyLarge data setsGeometrical procedureObserved variablesCorrelated variablesAnalysis modelGeneral approachLatent variablesFactor modelingLatent factorsStrong prior beliefsUnderlying structureData setsPrincipal component analysisModelVariablesRegulatory networksLarge numberPrior beliefs
2010
Bayesian Methods in Genomics and Proteomics Studies
Sun N, Zhao H. Bayesian Methods in Genomics and Proteomics Studies. 2010, 125-136. DOI: 10.1002/9780470669716.ch6.Peer-Reviewed Original Research
2008
Is Subcellular Localization Informative for Modeling Protein‐Protein Interaction Signal?
Liu J, Zhao H, Tan J, Luo D, Yu W, Harner E, Shih W. Is Subcellular Localization Informative for Modeling Protein‐Protein Interaction Signal? Journal Of Electrical And Computer Engineering 2008, 2008 DOI: 10.1155/2008/365152.Peer-Reviewed Original ResearchComplex regulatory networkSubcellular localization dataMultiple biological sourcesRegulatory networksSubcellular compartmentsSubcellular localizationPPI predictionGenomic signal processingLocalization dataBiological sourcesInteraction signalsProteinStatistical feasibilitySaccharomycesYeastRecent workCompartmentsLocalization
2006
A Misclassification Model for Inferring Transcriptional Regulatory Networks
Vannucci M, Sun N, Zhao H. A Misclassification Model for Inferring Transcriptional Regulatory Networks. 2006, 347-365. DOI: 10.1017/cbo9780511584589.019.Peer-Reviewed Original ResearchTranscriptional regulatory networksGene expression dataRegulatory networksExpression dataUnderlying transcriptional regulatory networksProtein-DNA binding dataNetwork reconstructionSet of proteinsYeast cell cycleMutual regulatory interactionsRegulatory network reconstructionGene regulationRegulatory interactionsSpecific genesCell cycleGenesBiological researchExpression levelsProteinTRNBinding dataHigh connectivityTransient stimulationRecent advancesStatistical framework
2005
Integrating mRNA Decay Information into Co-Regulation Study
Chen L, Zhao H. Integrating mRNA Decay Information into Co-Regulation Study. Journal Of Computer Science And Technology 2005, 20: 434-438. DOI: 10.1007/s11390-005-0434-1.Peer-Reviewed Original ResearchMRNA decay ratesTranscript amountsTranscription rateBioinformatics analysisTranscriptional regulatory networksCo-regulated genesRelative transcript amountsMRNA degradation ratesHigh-throughput technologiesGene regulationGenomic signalsRegulatory networksDifferent genesGene clusteringMRNA synthesisMRNA transcriptsDownstream analysisGenesDNAMotifSimilarity analysisTranscriptsRegulationIdentification
This site is protected by hCaptcha and its Privacy Policy and Terms of Service apply