Xiting Yan, PhD
Associate Professor of Medicine (Pulmonary, Critical Care and Sleep Medicine); Director of Data Analysis and Bioinformatics Hub, The Center for Precision Pulmonary Medicine (P2MED); Assistant Professor, Biostatistics
Biography
Research & Publications
News
Appointments
Biography
Dr. Yan received doctoral degrees in both applied statistics and computational biology and bioinformatics. She is interested in genetics, genomics, computational biology, biostatistics, system biology and bioinformatics. Her current research topics include (1) understanding disease heterogeneity and pathogenesis using large-scale omics data at both bulk and single cell resolution and (2) developing novel statistical and computational methods for analyses of different types of omics data and the integration of them with drug perturbation data for potential personalized treatment design.
Education & Training
- Postdoctoral AssociateYale School of Medicine (2010)
- PhDUniversity of Southern California, Biological Science Department/Computational Biology and Bioinformatics (2009)
- PhDPeking University, Department of Probability and Statistics, School of Mathematical Sciences/Applied Statistics (2006)
- BSPeking University, Department of Probability and Statistics, School of Mathematical Sciences/Probability and Statistics (2001)
Activities
- A Hybrid Machine Learning and regression Method for Cell Type Deconvolution of Spatial Barcoding-based Transcriptomic dataToronto, ON, Canada 2023JSM 2023
- Spatial Deconvolution Method Considering Platform Effect Removal, Sparsity and Spatial InformationIt's a presentation on zoom. 2023Spring 2023 Seminar Series of Department of Biomedical Informatics at Ohio State University
- A Hybrid Machine Learning and regression Method for Cell Type Deconvolution of Spatial Barcoding-based Transcriptomic dataLos Angeles, CA, United States 2022American Society of Human Genetics Annual Meeting 2022
- Statistical Challenges in Analyses of Single Cell RNA Sequencing Data and Spatial Transcriptomic DataIt was a presentation on zoom. 2022Seminar of Nevada Institute of Personalized Medicine at University of Nevada Las Vegas
- Idiopathic Pulmonary Fibrosis at Single-Cell ResolASN Kidney Week 2020 2020Idiopathic Pulmonary Fibrosis at Single-Cell Resol
- Statistical Modeling in Single Cell Genomics DataShanghai, Shanghai, China 2019Statistical Modeling in Single Cell Genomics Data
- Statistical challenges in single cell RNA sequencing data analysisTianjin, Tianjin, China 2019Statistical challenges in single cell RNA sequencing data analysis
- Cell Lineage Defined By Single Cell Transcriptomics Of The Sputum In AsthmaDallas, TX, United States 2019Cell Lineage Defined By Single Cell Transcriptomics Of The Sputum In Asthma
- Pathway based clustering of longitudinal RNAseq of induced sputum in asthma patients reveals stable transcriptional endotypes of asthmaWashington, DC, United States 2017ATS 2017
- Longitudinal RNA Sequencing Data of Induced Sputum in Asthma Patients Reveals Stable Transcriptional Endotypes of Asthma Associated with Asthma SeverityKeystone, CO, United States 2017Keystone Symposia: Asthma: From Pathway Biology to Precision Therapeutics
- Longitudinal RNA sequencing data of induced sputum in asthma patients reveals stable transcriptional endotypes of asthma associated with asthma severityWashington, DC, United States 2017Longitudinal RNA sequencing data of induced sputum in asthma patients reveals stable transcriptional endotypes of asthma associated with asthma severity
- Noninvasive Analysis of the Sputum Transcriptome Discriminates Clinical Phenotypes of AsthmaAllergy, Immunology & Inflammation Webinar Journal Club 2016Noninvasive Analysis of the Sputum Transcriptome Discriminates Clinical Phenotypes of Asthma
- Longitudinal RNA sequencing data of induced sputum in asthma patients reveals stable transcriptional endotypes of asthma associated with asthma severityKeystone, CO, United States 2016Longitudinal RNA sequencing data of induced sputum in asthma patients reveals stable transcriptional endotypes of asthma associated with asthma severity
- Gene Expression Analysis Pipeline for Ion Torrent RNAseq DataDenver, CO, United States 2015American Thoracic Society 2015 International Conference
- RNAseq in Sarcoidosis and Alpha-1 Antitrypsin Deficiency PatientsDenver, CO, United States 2015American Thoracic Society 2015 International Conference
- Non-invasive Analysis of the Airway Transcriptome Discriminates Clinical Phenotypes of AsthmaDenver, CO, United States 2015American Thoracic Society 2015 International Conference
- Non-invasive Analysis of the Sputum Transcriptome Discriminates Clinical Phenotypes of AsthmaWashington, DC, United States 2015Translational Science Meeting 2015
- Identifying Asthma Heterogeneity from Gene Expression Data by Integrating Pathway InformationResearch Triangle Park, United States 20152014-15: Bioinformatics: Statistical and Computational Challenges in Omics Data Integration Workshop
- Identifying Asthma Heterogeneity from Gene Expression Data by Integrating Pathway InformationUniversity, NC, United States 2015Identifying Asthma Heterogeneity from Gene Expression Data by Integrating Pathway Information
- Non-invasive Analysis of the Airway Transcriptome Discriminates Clinical Phenotypes of AsthmaAspen, CO, United States 2015Non-invasive Analysis of the Airway Transcriptome Discriminates Clinical Phenotypes of Asthma
- Non-invasive Analysis of the Airway Transcriptome Discriminates Clinical Phenotypes of AsthmaDenver, CO, United States 2015Non-invasive Analysis of the Airway Transcriptome Discriminates Clinical Phenotypes of Asthma
Honors & Recognition
| Award | Awarding Organization | Date |
|---|---|---|
| The YCCI Scholar Award, Yale University School of Medicine | Yale Center for Clinical Investigation | 2014 |
Professional Service
| Organization | Role | Date |
|---|---|---|
| The Journal of Allergy and Clinical Immunology | Reviewer | 2016 - Present |
| BMC Bioinformatics | Reviewer | 2009 - Present |
| Bioinformatics | Reviewer | 2009 - Present |