Ming (Tommy) Tang

  • Senior Scientist
  • Dana Farber Cancer Institute

Title of the talk: Reproducible research in genomic data science



“I am a computational biologist in cancer research with expertise in analyzing large-scale bulk sequencing data, single-cell transcriptomic and epigenomics data, and developing bioinformatics tools. My primary research interest is to generate and refine hypotheses in cancer research and discover biomarkers for immunotherapy through integrative data analysis. I am currently a senior scientist in the Data Science department at Dana-Farber Cancer Institute leading the bioinformatics effort for the Cancer Immunologic Data Commons as part of the NCI Cancer Moonshot project on cancer immunotherapy, and responsible for the development of the ATAC-seq analysis pipeline. I am into reproducible research. With docker/singularity and Rmarkdown notebook, I try to make my analysis reproducible as much as possible. In addition, I write extensive documentation for my software and data analysis.”