CSCI2950-C: Algorithms for Cancer Genomics
Spring 2015

Professor: Ben Raphael

Time: Tuesday/Thursday 10:30-11:50am [CIT 245]


This course seminar will explore algorithmic challenges that emerge in the analysis and interpretation of cancer genome sequencing data, with a focus on two major themes.

  • The mutational process of cancer evolution. The underlying algorithmic problem is to construct trees that represent the relationships between cells from mutational data. We will explore tree reconstruction algorithms using phylogenetic techniques (perfect phylogeny and Dollo parsimony) and population genetic techniques (branching processes and the coalescent).
  • The identification of combinations of cancer causing mutations. Such combinations typically result from biological interactions between genes, which are represented via graphs, or networks. We will examine algorithms to analyze data on graphs including random walks (e.g. PageRank), diffusion processes, community detection, and spectral methods for graph partitioning.
  • Course Organization



    Outline of Topics



    Proposal:Due TBD (Specific Aims and Significance) and TBD (All).

    Paper Reviews

    Course Credits (for Computer Science students)


    Previous offerings of this course are available here: