The Pejaver Laboratory
We develop, adapt and apply machine learning methods to relate genetic
variation to molecular function and disease using secondary biomedical data sets
What We Do
Genome Interpretation
We integrate functional annotations and predictions to infer the impact of genetic variants individually and jointly over a genome on molecular and organismal phenotypes
Data-driven Phenotyping
We extract and model information from electronic health records (EHRs) to derive quantitative definitions of disease to aid in biomedical discovery and clinical diagnosis
Applied Machine Learning
We develop and adapt machine learning approaches that specifically address challenges relevant to biomedical data such as noise, bias and limited availability