The schedule for the rest of the seminar is as follows.

• March 14: Written report deadline. Send it to me by email.

Presentations (note, the order of the two first presentations changed, March 6) 

• March 18: Network motif discovery by color coding
• March 25: Identifying conserved pathways by network alignment
• April 1: Network deconvolution
• April 8: Linking genes and diseases via network propagation

Introductory slides including topic proposals can be found here.

A network (a weighted graph) is often used as a high-level abstraction of pairwise interactions or dependencies between biological entities such as genes, proteins, or metabolites. These networks are growing rapidly as high-throughput technologies now enable measuring large numbers of interactions in parallel. However, extracting biologically meaningful knowledge from such networks is far from easy.  Formalizing biological problems as graph problems can be challenging. Also, experimental noise may introduce large numbers of spurious and missing edges to the network or the experimental technique may not distinguish between direct and indirect effects making the interpretation of the network difficult. In this seminar we will explore how networks are used to analyze large biological data sets.

• construction
• alignment
• querying
• motif discovery 
• clustering
• deconvolution