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Network Inference Module Guide

The network inference module provides a brief introduction to the problem of automatically inferring gene regulatory networks from high-throughput data. I do not know of any appropriate textbook for tutorial for this rapidly changing field, so we’ll have to rely on a few papers from the scientific literature.

Before Day 1 class

• Read and think about this Ideker paper.
• Write 150-250 words about the Ideker paper. Start by explaining the most important take-home message or messages. Mention the ways in which the authors attempted to support these messages, but don’t get caught up in details. Follow with your opinions about the messages and the extent to which the paper did or did not support those messages.

Day 1: Monday, November 2, 2009

In class

· Talk about networks, using the GAL network as an example.

· Talk about data types used in the Ideker paper as well as other high-throughput types.

· Discuss your analyses of the Ideker paper.

· Talk about automating the process described in the paper.

· Do a toy example by hand.

Before the next class

• Read and think about this paper by Brian Haynes and me.
• There will likely be things in this paper you don’t understand. Bring to class a written list of questions to discuss and turn in. If you understand everything, write down some questions that you think other people might have and the answers to them.

Day 2: Friday, November 6, 2009

• Start going through the formalisms and methods used in the Haynes paper.

Day 3: Moday, November 9, 2009

• Continue going through the formalisms and methods used in the Haynes paper.

In case you are interested, here are some PowerPoint slides that Brian Haynes made when he lectured to this class on network discovery last year. I am not sure they will be useful to you, but here they are just in case.