Breast Oncology Center Computational Biology (BCCB)

The Breast Oncology Center Computational Biology (BCCB) group leads the computational biology efforts at Dana-Farber Cancer Institute's Breast Oncology Center to characterize multi-omics sequencing datasets that describe the genetic changes that occur across breast cancer. This characterization is done by applying existing and novel computational biology, bioinformatic, and machine learning algorithms to sequencing datasets and correlating them with multi-dimensional clinical datasets that contain treatment and diagnostic information. The aim of these efforts is to identify genomic alterations and transcriptional changes associated with tumor evolutionary dynamics, mechanisms of resistance, and therapeutic benefit. These datasets and multi-omics associations could help identify novel approaches for personalized care in oncology. In addition, this datasets and association may provide support for new methods in clinical decision-making, tumor markers for rational drug development, and new insights into tumor biology through innovative analyses.

Mission

• Lead or support the computational biology efforts for the correlative analyses of investigator-initiated trials and cohort studies.
• Provide computational biology support from raw or preprocessed genomic data to final analysis with correlations to clinical data.
• Provide expertise in a broad range of multi-omics and spatial technologies (RNA-seq, DNA-seq, single cell, ctDNA) and analysis methods.
• Work closely with the PI, cohort-study, data abstractor, data programming, and biostats teams.