Xueting (Leona) Wang
About
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Titles
PhD Student, Computational Biology & Bioinformatics
Biography
Xueting (Leona) Wang is currently a PhD student in the Biological & Biomedical Sciences program, track of Computational Biology and Biomedical Informatics.
After completing her M.D. degree at Shanghai Jiaotong University, she discovered her passion for biomedical data science. She further honed her skills in biostatistics during her master's study at Yale School of Public Health. Throughout her master's study, she collaborated with biostatisticians and clinicians to analyze electronic health records (EHR) and design clinical trials.
As she embarks on her Ph.D. studies, she wishes to continue her focus on methodology and analysis research on EHR. When not studying, she is a big fan of painting and hanging out with friends.
Education & Training
- MPH
- Yale University, Biostatistics
- MD
- Shanghai JiaoTong University, Clinical Medicine
Research
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Overview
Public Health Interests
ORCID
0000-0002-1005-3072
Research at a Glance
Yale Co-Authors
Publications Timeline
Wei Wei, PhD
David Rimm, MD, PhD
Harriet Kluger, MD
Jeffrey Ishizuka, MD, DPhil
Thazin Nwe Aung, PhD
William Damsky, MD, PhD
Publications
2025
Identification of Serum Metabolites to Improve Diagnostic Efficacy in Pulmonary Embolism
Chen S, Xu X, Li X, Qin Q, Zhu G, Yu H, Du K, Wang X, Ye W, Gu W. Identification of Serum Metabolites to Improve Diagnostic Efficacy in Pulmonary Embolism. Journal Of Proteome Research 2025, 24: 1885-1894. PMID: 40128110, DOI: 10.1021/acs.jproteome.4c00863.Peer-Reviewed Original ResearchCitationsMeSH Keywords and ConceptsConceptsGas chromatography-mass spectrometryPulmonary embolismDiagnostic efficacyHigh-throughput metabolomics methodPE patientsValidation cohortSerum metabolic profilesUnsupervised principal component analysisDiscovery cohortMetabolic profileHealthy individualsChromatography-mass spectrometryD-dimer levelsMetabolomics methodMultivariate data analysisPLS-DALife-threatening diseaseD-dimerClinical indicationsHealthy controlsBiomarker panelEmbolizationSerum metabolitesCohortPotential biomarkers
2024
rBMA: A robust Bayesian Model Averaging Method for phase II basket trials based on informative mixture priors
Wang X, Wei W. rBMA: A robust Bayesian Model Averaging Method for phase II basket trials based on informative mixture priors. Contemporary Clinical Trials 2024, 140: 107505. PMID: 38521384, DOI: 10.1016/j.cct.2024.107505.Peer-Reviewed Original ResearchMeSH Keywords and ConceptsConceptsPhase II basket trialRobust Bayesian modelBasket trial designBiomarker-defined subgroupsMixture priorsBinary endpointsModel averaging methodPosterior distributionBayesian modelBasket trialsSimulation studyEra of targeted therapyDevelopment of targeted agentsPriorsAverage methodGenomic alterationsPatient populationNovel treatmentAntitumor activityPosterior weightsEarly phase oncology trialsStatistical powerOncology trialsTrial designTrialsMesenchymal Stromal Cell Therapy Alleviates Ovalbumin-Induced Chronic Airway Remodeling by Suppressing M2 Macrophage Polarization
Yu H, Zhu G, Qin Q, Wang X, Guo X, Gu W. Mesenchymal Stromal Cell Therapy Alleviates Ovalbumin-Induced Chronic Airway Remodeling by Suppressing M2 Macrophage Polarization. Inflammation 2024, 47: 1298-1312. PMID: 38316671, DOI: 10.1007/s10753-024-01977-9.Peer-Reviewed Original ResearchCitationsAltmetricConceptsSuppressed macrophage M2 polarizationEffect of mesenchymal stromal/stem cellsMesenchymal stromal/stem cellsChronic airway remodelingAirway remodelingChronic asthmaTherapeutic effects of mesenchymal stromal/stem cellsMacrophage M2 polarizationMouse modelModel of chronic asthmaMouse model of chronic asthmaTh2 cytokine levelsTransforming growth factor-bM2 polarizationMechanisms of airway remodelingInflammatory cell infiltrationInhibition of ER stressSuppressing M2 macrophage polarizationER stressGrowth factor BOxidative stressPhenotype of macrophagesAnti-inflammatory effectsM2 macrophage polarizationAirway hyperresponsiveness
2023
Subsets of IFN Signaling Predict Response to Immune Checkpoint Blockade in Patients with Melanoma.
Horowitch B, Lee D, Ding M, Martinez-Morilla S, Aung T, Ouerghi F, Wang X, Wei W, Damsky W, Sznol M, Kluger H, Rimm D, Ishizuka J. Subsets of IFN Signaling Predict Response to Immune Checkpoint Blockade in Patients with Melanoma. Clinical Cancer Research 2023, 29: 2908-2918. PMID: 37233452, PMCID: PMC10524955, DOI: 10.1158/1078-0432.ccr-23-0215.Peer-Reviewed Original ResearchCitationsAltmetricMeSH Keywords and ConceptsConceptsImmune checkpoint inhibitorsHuman melanoma cell linesMelanoma cell linesPD-L1Validation cohortYale-New Haven HospitalCombination of ipilimumabPD-L1 markersImmune checkpoint blockadePD-L1 biomarkerNew Haven HospitalSTAT1 levelsCell linesWestern blot analysisCheckpoint inhibitorsCheckpoint blockadeClinical responseOverall survivalImproved survivalResistance of cancersMetastatic melanomaMelanoma responsePredict responseTreatment responseDistinct patterns
2020
p62-dependent autophagy in airway smooth muscle cells regulates metabolic reprogramming and promotes airway remodeling
Yu H, Cheng Y, Zhang G, Wang X, Gu W, Guo X. p62-dependent autophagy in airway smooth muscle cells regulates metabolic reprogramming and promotes airway remodeling. Life Sciences 2020, 266: 118884. PMID: 33310038, DOI: 10.1016/j.lfs.2020.118884.Peer-Reviewed Original ResearchCitationsMeSH Keywords and ConceptsConceptsKnockdown of p62Mechanism of p62Bronchial smooth muscle cellsP62-dependent autophagyIncreased p62 expressionP62 expressionAirway remodelingGlucose consumptionAutophagy fluxAutophagic fluxCCK8 assayP62 overexpressionTranswell methodP62Glycolytic genesGlycolytic proteinsLactate productionMetabolic reprogrammingMigration in vitroHuman bronchial smooth muscle cellsBSMC proliferationCell migrationSmooth muscle cellsAirway remodeling processPromote airway remodelingResearch progress of metabolomics in bronchial asthma
Wang X, Gu W. Research progress of metabolomics in bronchial asthma. International Journal Of Respiration 2020, 40: 847-852. DOI: 10.3760/cma.j.cn131368-20190318-00378.Peer-Reviewed Original ResearchConceptsProgress of metabolomicsMethods of metabolomicsVariable expiratory airflow limitationHistory of respiratory symptomsLow molecular weight metabolitesExpiratory airflow limitationHeterogeneity of asthmaAspects of diagnosisChronic respiratory diseasesAirflow limitationMetabolomicsRespiratory symptomsBronchial asthmaPathology in vivoMetabolite fluctuationsAsthmaResearch progressRespiratory diseaseDiseasePhenotypeMetabolitesDiagnosisSymptomsDrugPathology
2019
Detection of pulmonary ground-glass opacity based on deep learning computer artificial intelligence
Ye W, Gu W, Guo X, Yi P, Meng Y, Han F, Yu L, Chen Y, Zhang G, Wang X. Detection of pulmonary ground-glass opacity based on deep learning computer artificial intelligence. BioMedical Engineering OnLine 2019, 18: 6. PMID: 30670024, PMCID: PMC6343356, DOI: 10.1186/s12938-019-0627-4.Peer-Reviewed Original ResearchCitationsAltmetricMeSH Keywords and ConceptsMeSH KeywordsAlgorithmsDatabases, FactualDeep LearningDiagnosis, Computer-AssistedFalse Positive ReactionsHumansImage Processing, Computer-AssistedLungLung NeoplasmsRadiographic Image Interpretation, Computer-AssistedRadiologyReproducibility of ResultsSensitivity and SpecificitySolitary Pulmonary NoduleTomography, X-Ray ComputedConceptsDeep learningF-scoreLung Image Database Consortium and Image Database Resource Initiative (LIDC-IDRI) databaseMethod of deep learningArtificial intelligence systemsInput imageNetwork trainingDetect pulmonary nodulesIdentification of lung nodulesIntelligent systemsNodule classificationGround-glass opacity imagesPreprocessing methodsDetect ground-glass opacitiesEvaluation resultsLearningAccuracyAlexNetResNet50PreprocessingImagesThree-dimensional featuresGround-glass opacitiesNetworkFeatures
Academic Achievements & Community Involvement
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Honors
honor Gruber Science Fellowship
09/01/2023Yale University AwardGruber FoundationDetailsUnited States