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INFORMATION FOR

Xiting Yan, PhD

Assistant Professor of Pulmonary and Biostatistics; Director of Data Analysis and Bioinformatics Hub, The Center for Precision Pulmonary Medicine (P2MED)

Contact Information

Xiting Yan, PhD

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 to better understand disease pathogenesis for potential personalized treatment design.

Education & Training

  • Postdoctoral Associate
    Yale School of Medicine (2010)
  • PhD
    University of Southern California, Biological Science Department/Computational Biology and Bioinformatics (2009)
  • PhD
    Peking University, Department of Probability and Statistics, School of Mathematical Sciences/Applied Statistics (2006)
  • BS
    Peking 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 data
    Los Angeles, CA, United States 2022
    American Society of Human Genetics Annual Meeting 2022
  • Statistical Challenges in Analyses of Single Cell RNA Sequencing Data and Spatial Transcriptomic Data
    It was a presentation on zoom. 2022
    Seminar of Nevada Institute of Personalized Medicine at University of Nevada Las Vegas
  • Idiopathic Pulmonary Fibrosis at Single-Cell Resol
    ASN Kidney Week 2020 2020
    Idiopathic Pulmonary Fibrosis at Single-Cell Resol
  • Statistical challenges in single cell RNA sequencing data analysis
    Tianjin, Tianjin, China 2019
    Statistical challenges in single cell RNA sequencing data analysis
  • Cell Lineage Defined By Single Cell Transcriptomics Of The Sputum In Asthma
    Dallas, TX, United States 2019
    Cell 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 asthma
    Washington, DC, United States 2017
    ATS 2017
  • Longitudinal RNA Sequencing Data of Induced Sputum in Asthma Patients Reveals Stable Transcriptional Endotypes of Asthma Associated with Asthma Severity
    Keystone, CO, United States 2017
    Keystone 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 severity
    Washington, DC, United States 2017
    Longitudinal 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 Asthma
    Allergy, Immunology & Inflammation Webinar Journal Club 2016
    Noninvasive 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 severity
    Keystone, CO, United States 2016
    Longitudinal 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 Data
    Denver, CO, United States 2015
    American Thoracic Society 2015 International Conference
  • RNAseq in Sarcoidosis and Alpha-1 Antitrypsin Deficiency Patients
    Denver, CO, United States 2015
    American Thoracic Society 2015 International Conference
  • Non-invasive Analysis of the Airway Transcriptome Discriminates Clinical Phenotypes of Asthma
    Denver, CO, United States 2015
    American Thoracic Society 2015 International Conference
  • Non-invasive Analysis of the Sputum Transcriptome Discriminates Clinical Phenotypes of Asthma
    Washington, DC, United States 2015
    Translational Science Meeting 2015
  • Identifying Asthma Heterogeneity from Gene Expression Data by Integrating Pathway Information
    Research Triangle Park, United States 2015
    2014-15: Bioinformatics: Statistical and Computational Challenges in Omics Data Integration Workshop
  • Identifying Asthma Heterogeneity from Gene Expression Data by Integrating Pathway Information
    University, NC, United States 2015
    Identifying Asthma Heterogeneity from Gene Expression Data by Integrating Pathway Information
  • Non-invasive Analysis of the Airway Transcriptome Discriminates Clinical Phenotypes of Asthma
    Aspen, CO, United States 2015
    Non-invasive Analysis of the Airway Transcriptome Discriminates Clinical Phenotypes of Asthma
  • Non-invasive Analysis of the Airway Transcriptome Discriminates Clinical Phenotypes of Asthma
    Denver, CO, United States 2015
    Non-invasive Analysis of the Airway Transcriptome Discriminates Clinical Phenotypes of Asthma

Honors & Recognition

AwardAwarding OrganizationDate
The YCCI Scholar Award, Yale University School of MedicineYale Center for Clinical Investigation2014

Professional Service

OrganizationRoleDate
The Journal of Allergy and Clinical ImmunologyReviewer2016 - Present
BMC BioinformaticsReviewer2009 - Present
BioinformaticsReviewer2009 - Present

Departments & Organizations