Quantitative Methods

New medical breakthroughs, as well as the effective management of health care in the future, require the integration of data and methods across the different realms of fundamental research, development of therapeutics, and health care practice. Faculty at the University of Connecticut’s Center for Quantitative Medicine (CQM) are available to contact with inquiries about consultations in quantitative methods.


The Center for Quantitative Medicine (CQM)
The mission of CQM, established in 2013, is to help make the integration of data and methods a reality. CQM provides a formal common environment to bring together faculty who use quantitative methods to impact human health. Faculty within the Center conduct research in systems biology, systems medicine, and systems pharmacology, using mathematical tools to study molecular networks and multi-scale systems; genomics, using analysis of high-throughput data sets; bioinformatics, developing databases and computational tools for the analysis of a broad range of biological information; biomedical informatics, including the organization and analysis of large clinical data sets; biostatistics, including the development of statistical methods for the analysis of large data sets; and other quantitative approaches to human health, including methods in public health, epidemiology, and the development of appropriate evaluation methods for health care-related processes and policies.

Broadly, the expertise of CQM faculty and staff includes:

  • Use of advanced mathematical and statistical techniques for the analysis of data, ranging from the molecular and cellular scales, such as transcriptomics, metabolomics, or flow cytometry data, to the patient and population scales, including claims and clinical data, among others.
  • Domain knowledge in the clinical, health economics, and health policy arenas.
  • Predictive modeling across scales, using a wide range of modeling platforms. Application of systems approaches to processes that involve several scales, such as individual and population, or molecular and organism scales.