Liang Lab
Our research focuses on developing the computational and statistical tools for analyses of multi-omics data to understand the biological mechanism for diseases and provide prediction model to assess future risk and individual benefit for intervention.
Building 2, Room 249A
Harvard T.H. Chan School of Public Health
Our Focus
We are a lab joined by enthusiastic faculty members, postdocs and students interested in developing efficient computational tools and design novel applications to under the biological mechanism of complex diseases and develop useful prediction models for disease risk or exposures of interest.
We leverage large-scale multi-omics datasets in longitudinal cohorts and employ novel epidemiological and biostatistical approaches to achieve these goals. A typical example can be found in the publication of Li et al. in the European Heart Journal (2020) and subsequent publications from our group, where we developed novel metabolomic signatures for dietary index and demonstrated their stronger association to cardiometabolic diseases as compared to traditional dietary assessment.
What We Do
Traditional method assess dietary pattern by questionnaire such as Food Frequency Questionnaire (FFQ) or 24-hour recall. However, these methods are subject to bias and measurement errors. Metabolomics in plasma, for example, can objectively reflect what has been eating in the past and may be more accurately representing the type and amount of food intake.
Our Research
Featured Publications
Lab Photos
Links and Resources
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