JLAB.BU.EDU

The focus of our research is to develop computational and statistical tools to investigate core components that contribute to disease prognosis and etiology, and for the accurate determination of optimal diagnostic, prognostic, and therapeutic regimens for individual patients. We are actively developing methods and software tools for data preprocessing, integration, and downstream analysis, and applying these tools in a variety of clinical and biomedical applications. Our work includes a balance between statistical methods development, algorithm optimization, and clinical application. Statistical innovation in our group focuses on the development of clinically motivated tools that integrate linear modeling, Bayesian methods, factor analysis and structural equations models, Hidden Markov models, mixture models, dynamic programming, and high-performance parallel computing. This work has resulted in widely-used tools and algorithms for profiling transcription factors (MAT, MA2C),..

Primary location: Boston United States