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Dr Yanchun Bao Research Fellow, University of Essex

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Email
ybaoa@essex.ac.uk
Telephone
01206 874780
Office
2N2.5A.17
Curriculum vitae

I am a Research fellow working in Understanding Society Biomarker Project and MiSoc Project. My current research is to apply and develope statistical methods using genetic information to understand the causal effect of exposure to health/social/economic outcomes. I also help to disseminate Understanding Society Genetic/Epigenetic data. Any informal enquiry about Understanding Society Genetic/Epigenetic data could send to our group email address:  genetics@understandingsociety.ac.uk.

My research interests are:

  • Causal pathway through mediators with genetic instrument
  • Instrumental Variables Methods (Mendelian Randomisation)  
  • Methods of Casual analysis
  • Longitudinal data analysis
  • Survival data analysis
  • Next generation data analysis (Hidden Markov / Random Field Model)
  • Epidemiology and life-course study in Ophthalmology research
  • Covariance model

 

 

 


Publications

Displaying all 13 publications

  1. Socioeconomic position and DNA methylation age acceleration across the lifecourse

    Amanda Hughes, Melissa Smart, Tyler Gorrie-Stone, et al.

    1. Health
    2. Life Course Analysis
    3. Social Stratification
    4. Genetics
  2. Gene discovery and polygenic prediction from a genome-wide association study of educational attainment in 1.1 million individuals

    James J. Lee, Robbee Wedow, Aysu Okbay, et al.

    1. Biology
    2. Genetics
  3. A comparison of robust methods for Mendelian randomization using multiple genetic variants

    Yanchun Bao, Paul Clarke, Melissa Smart, et al.

    1. Income Dynamics
    2. Biology
    3. Genetics
  4. Leveraging DNA methylation quantitative trait loci to characterize the relationship between methylomic variation, gene expression and complex traits

    Eilis Hannon, Tyler J. Gorrie-Stone, Melissa Smart, et al.

    1. Science And Technology
    2. Research
    3. Health
    4. Biology
    5. Genetics
  5. Linear transformation models for censored data under truncation

    Huan Wang, Hongsheng Dai, Marialuisa Restaino, et al.

  6. Predicting gene expression from genome wide protein binding profiles

    Mohsina M. Ferdous, Yanchun Bao, Veronica Vinciotti, et al.

    1. Computing
    2. Science And Technology
    3. Research
    4. Genetics
  7. Gene-environment interactions between education and body mass: evidence from the UK and Finland

    Vikesh Amin, Petri Böckerman, Jutta Viinikainen, et al.

    1. Education
    2. Health
    3. Biology
    4. Genetics
  8. Vitamin D and cognitive function: a Mendelian randomisation study

    Jane Maddock, Ang Zhou, Alana Cavadino, et al.

    1. Older People
    2. Psychology
    3. Science And Technology
    4. Health
    5. Life Course Analysis
    6. Genetics
  9. BMI and well-being - a Mendelian Randomization study

    Yanchun Bao

    1. Well Being
    2. Health
    3. Biology
    4. Genetics
  10. Combining multiple SNPs in Mendelian randomization studies with continuous outcome

    Yanchun Bao

    1. Health
    2. Biology
    3. Genetics
  11. Genome-wide analysis of health-related biomarkers in the UK Household Longitudinal Study reveals novel associations

    Bram P. Prins, Karoline B. Kuchenbaecker, Yanchun Bao, et al.

    1. Science And Technology
    2. Health
    3. Biology
    4. Genetics
  12. Multivariate genome-wide and integrated transcriptome and epigenome-wide analyses of the well-being spectrum

    Bart M. L. Baselmans, Rick Jansen, Hill Fung Ip, et al.

    1. Psychology
    2. Medicine
    3. Science And Technology
    4. Well Being
    5. Health
    6. Biology
    7. Genetics
  13. PCSK9 genetic variants and risk of type 2 diabetes: a mendelian randomisation study

    Amand F. Schmidt, Daniel I. Swerdlow, Michael V. Holmes, et al.

    1. Medicine
    2. Science And Technology
    3. Health
    4. Biology

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