Functional Genomics and Computational Biology Lab

This group focuses on the application of functional genomics techniques and the development of computational approaches to create a comprehensive view of human diseases.

Dana-Farber/Harvard Cancer Center (DF/HCC)

The DF/HCC is a 7-institution Boston-based consortium where cancer research and treatment collaborations combine the disciplines of population science, clinical science, and basic research to facilitate the development of novel and improved modalities for the prevention and treatment of cancer.

Eastern Cooperative Oncology Group (ECOG)

As one of the largest clinical cancer research organizations in the US, ECOG conducts clinical trials in all types of adult cancers.

International Breast Cancer Study Group (IBCSG)

IBCSG dedicates itself to the development of innovative clinical research to improve the quality of life and survival of women with breast cancer.

Center for Cancer Computational Biology (CCCB)

The mission of the CCCB is to further the Institute’s commitment to advance the understanding, diagnosis, treatment, cure, and prevention of cancer and related diseases. We aim to do that by providing broad-based support for the analysis and interpretation of ‘omic data and in doing so further basic, clinical, and translational research and to conduct research that opens new ways of understanding human cancer.

CanCORS

This group conducts population-based research in the areas of access to care, patterns of care, and prognosis for lung and colorectal cancer.

dChip

DNA-Chip Analyzer is a software package implementing model-based expression analysis of oligo nucleotide arrays and several high-level analysis procedures.

X. Shirley Liu Lab

Dr. Liu's lab focuses on design of statistical and computational algorithms to discover and explore the genomic sequence elements related to gene regulations.

Cheng Li Lab

This lab develops statistical methodologies to address medical and public health issues arising from population-based cancer studies.

This lab develops statistical and computational methodologies for genomic data analysis and integration, with the aim to understand systems-level gene regulatory mechanisms.