Yao Lab In the Department of Obstetrics & Gynecology

Translational Research

Our motivations for building this translational research program are to use paradigms in developmental biology, statistics and reproductive medicine to advance care for patients who are suffering from infertility and use this knowledge to benefit other areas of medicine. We hypothesize that maternal, paternal and embryonic factors can be used to determine prognosis in in vitro fertilization (IVF) treatment in terms of live birth rates. We previously applied regression tree analysis to identify non-redundant prognostic factors for positive pregnancy tests following IVF treatment. That work led to establishment of a prediction model for positive pregnancy test in IVF treatment (Jun et al., PLoS ONE 2008, Defining Human Embryo Phenotypes by Cohort-Specific Prognostic Factors).

In our ongoing interdisciplinary work with REI clinicians Drs. Lynn Westphal and Ruth Lathi, and the Wong Lab, we are constructing models to predict outcomes, such as live birth outcomes, that are critical to decision-making in infertility care.


  1. Provide infertility patients and their partners with the best available, personalized prediction for live birth rates in IVF. Personalized prognostic information derived from evidence-based, and rigorously validated algorithms is expected to empower patients, because it will support patients as they balance medical, emotional, and financial considerations in making decisions to build their families.
  2. Develop prognostic tools to propel the field of IVF for mechanism-driven prognostics, diagnostics and therapeutics.
  3. Apply what we learn about IVF prognostic factors to generate new hypotheses to our mouse embryo and reprogramming project.


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