Advanced Topics in Computer Science: Computational Methods for Single-cell and Spatial Biology

This seminar explores algorithmic, statistical, and machine learning challenges emerging from new technologies for measuring DNA, RNA, and molecular interactions from single cells and tissues. Topics include: clustering, dimensionality reduction and manifold learning for single-cell RNA sequencing and spatial transcriptomics data; inference of molecular interaction networks; temporal modeling of developmental processes; and phylogenetic tree reconstruction from single-cell DNA sequencing data. Seminar will include lectures and reading/discussion of recent research papers. Students complete a final project.