2022
Mendelian randomization for causal inference accounting for pleiotropy and sample structure using genome-wide summary statistics
Hu X, Zhao J, Lin Z, Wang Y, Peng H, Zhao H, Wan X, Yang C. Mendelian randomization for causal inference accounting for pleiotropy and sample structure using genome-wide summary statistics. Proceedings Of The National Academy Of Sciences Of The United States Of America 2022, 119: e2106858119. PMID: 35787050, PMCID: PMC9282238, DOI: 10.1073/pnas.2106858119.Peer-Reviewed Original Research
2011
Bayesian hierarchical modeling for signaling pathway inference from single cell interventional data
Luo R, Zhao H. Bayesian hierarchical modeling for signaling pathway inference from single cell interventional data. The Annals Of Applied Statistics 2011, 5: 725-745. PMID: 22162986, PMCID: PMC3233205, DOI: 10.1214/10-aoas425.Peer-Reviewed Original ResearchMarkov chain Monte CarloReal data analysisBayesian hierarchical modeling frameworkHierarchical modelingHierarchical modeling frameworkBayesian hierarchical modelingStatistical inferencePosterior distributionMonte CarloNetwork sparsitySimulation studyIntrinsic noiseModeling frameworkMeasurement errorInterventional dataInferenceMultiple protein activitiesPathway inferenceCarloModelingInterventional experimentsSuch dataSparsityData analysisNoise
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