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
2012
Time course RNA-seq: A potential avenue with somewhat different approach in tandem of differential analysis
Oh S, Zhao H, Noonan J. Time course RNA-seq: A potential avenue with somewhat different approach in tandem of differential analysis. 2012, 1: 580-587. DOI: 10.1109/cisis.2012.204.Peer-Reviewed Original ResearchMonte Carlo simulation studySimulation studyReal data setsStatistical frameworkDifferential expression methodsStatistical approachDependent dataMarkov model approachInherent dependenciesTime seriesModel approachHidden Markov Model ApproachStandard approachTime-series RNA-seq dataData setsIntuitive solutionBiological systemsTrajectory indexTemporal complexityDifferential analysisDifferent approachesApproachConsiderable advantagesSolution
This site is protected by hCaptcha and its Privacy Policy and Terms of Service apply