Due date Oct 22nd midnight. Please submit your critique as a pdf by email to Prof. Roy with subject “BMI826-023: Critique 1”
Please write a critique focusing on probabilistic graphical model-based methods used for the expression-based and prior-based network inference we have discussed. Your critique should be 1-2 pages long, single spaced. Your critique should include ideas and algorithms covered in the following papers:
- Using Bayesian Networks to Analyze Expression Data
- GENIE3 Dependency networks
- Reconstructing gene regulatory networks with bayesian networks by combining expression data with multiple sources of prior knowledge
- Robust data-driven incorporation of prior knowledge into the inference of dynamic regulatory networks
Please keep the following points in mind as you write your critique and address each in a separate section.
1. An overview of the general problem area these methods are addressing.
2. Briefly describe each method
3. How were the methods evaluated?
4. What novel insights were obtained using these methods?
5. What are the strengths and weaknesses of each method?
As an example, you can refer to these example critiques (Example1, Example2) that scored very highly. These critiques were written for a slightly different set of papers, but hopefully you can see these as examples of a good critique.