High-dimensional -omics data such as genomic, transcriptomic, and metabolomic data offer great promise in advancing precision medicine. In particular, such data have enabled the investigation of ...

Our lab has developed many data analysis workflows adapting and integrating sophisticated statistical methods to evaluate complex molecular datasets that we obtain with MS technologies. We are ...

Through tumor profiling and statistical analysis, precision oncology uses genomic and other biomarkers to drive discovery, drug development, and clinical care for patients with cancer. It intends to ...

The FDA’s new draft guidance on Bayesian methodology signals a shift toward more flexible, data-driven clinical trial designs, enabling sponsors to use prior data and adaptive approaches to improve ...

Data collected in psychiatry and related fields are complex because outcomes are rarely directly observed, there are multiple correlated repeated measures within individuals, and there is natural ...

A new statistical method provides a more efficient way to uncover biologically meaningful changes in genomic data that span multiple conditions -- such as cell types or tissues. A new statistical ...

What are your research topics? I develop statistical methods that help people make sense of complex and high-dimensional data — for example, information collected from many sensors, locations, or ...

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