Dean Lee Email & Phone Number

Cambridge, Massachusetts, United States

• Prepare data packages for multiple therapeutic modalities to credential targets, clarify mechanisms of resistance, and anticipate the influence of the tumor microenvironment (TME).
• Assess interpretable machine learning approaches to extract clinically predictive insights from large-scale omics data.
• Lead scRNA-seq data curation efforts. Standardize scRNA-seq data analysis workflow.

Cambridge, Massachusetts, United States

• Performed integrated analysis of scRNA-seq and scTCR-seq data from ex vivo tumor culture system.
• Led and mentored 6 computational biologists; managed 4 consultants/interns.
• Directed the production of single-cell immune reference map across dozens of tumor indications and autoimmune diseases via variational autoencoder-based integration.
• Facilitated the mining of single-cell immune reference map for novel drug targets to feed drug portfolio.
• Drove the effort to import new machine learning approaches to infer cell-cell interactions, predict efficacy of drug combinations, and enable joint analysis of scRNA-seq with bulk RNA-seq data, i.e. TCGA and GTEx.
• Prospected new data modalities to acquire for future use. Ex. spatial transcriptomics.

Cambridge, Massachusetts, United States

• Derived predictive biomarkers of response for two novel immunotherapies ahead of clinical trials.
• Standardized curation of public scRNA-seq data, now at 80+ studies and 6M+ single-cell transcriptomes.
• Implemented automated immune cell type calling method for scRNA-seq data.
• Collaborated with wet lab team to troubleshoot scRNA-seq and scTCR-seq experiments.

Cambridge, MA

• Addressed target expression, mechanism of action, and indication selection questions for the company’s entire preclinical drug portfolio.
• Validated proposed targets by mining external and internal scRNA-seq data.
• Established computational best practices for timely analysis of newly published datasets.

Cambridge, MA

• Identified previously overlooked differentially expressed genes from internal bulk RNA-seq dataset.
• Compiled molecular catalog of cell types in the mouse hypothalamus from scRNA-seq dataset.
• Established scRNA-seq statistical analysis pipeline with high-performance computing (HPC).
• Validated putative markers for specific hypothalamic neuron subtypes with multiplexed ISH.

Cambridge, MA

• Tested how selected transcription factors regulate the identity of cortical projection neurons in mice.
• Performed loss-of-function analyses in global and conditional knockout mice via immunohistochemistry and in situ hybridization.
• Performed gain-of-function analyses by ectopic overexpression of candidate genes via in utero electroporation of cloned genetic constructs.

HST 130: Neuroscience, Harvard Medical SchoolMCB 81: Fundamentals of Neuroscience, Harvard CollegeBIOS S-129: Stem Cell and Regenerative Biology, Harvard Extension School

Master'S Degree, Neuroscience

Master'S Degree, Applied Statistics

Bachelor Of Science (Bs), Neuroscience