The overall learning goals of this course is to provide a broad understanding of different network-based problems and computational algorithms to tackle these problems. The majority of these problems discussed in this class stem from Molecular Biology, however analogous problems arise in other complex systems. The content of the course is organized into five main sections:

  1. Representation and learning of molecular networks
  2. Context-specificity and Dynamics of networks
  3. Topological properties of networks
  4. Comparison of networks
  5. Network-based data integration and interpretation.

Please detailed syllabus for readings and topics here.