Genetic reverse engineering

Basso K, Margolin AA, Stolovitzky G, Klein U, Dalla-Favera R, Califano A. Reverse engineering of regulatory networks in human B cells. Nat Genet 2005 37 382-90. 

Houle I would like to offer an empirical confirmation of your basic point that things should look like a big mess when we try to reverse-engineer the brain. Developmental genetics has progressed to the point that we can test a lot of the simple predictions that are made on the basis of common sense, the same basis as the prediction of the modularity of mind. It would make sense for parts of the body that work together, such as the two jaws which developed separately, to be independent of the rest of development. This is not really the case (J. Mezey, personal communication). You might predict that early development would be less malleable evolutionarily than late development, and this is not true (Raff... 

Liang S, Furhman S, Somogyi R. Reveal, a general reverse engineering algorithm for inference of genetic network architectures. Pacific Symposium on Biocomputers 1998, pp. 18-29. 

Welcome to the future reverse engineering of genetic networks 130... 

Reverse engineering has been demonstrated to work in principle for model genetic networks of binary genes connected through logical rules [18]. A key issue is the data requirement necessary to provide sufficient information to capture the complexity of the molecular network. In model networks it has been shown that only a tiny subset of all possible behaviors need to be known in order to infer network architecture with accuracy [18], provided that the network exhibits significant constraints (biomolecular networks are far removed from randomly connected networks) [20]. 

Reverse engineering of a CNS genetic network using a linear model. Experimental gene expression data (circles development and injury), and simulation using a linear model (lines). Dotted line spinal cord, starting at day —11 (embryonic day 11). Solid line hippocampus development, starting at day... 

D haeseleer, R, S. Liang, and R. Somogyi. 2000. Genetic network inference From coexpression clustering to reverse engineering. Bioinformatics 16 707-26. 

Tegner, J., M. K. S. Yeung, J. Hasty, and J. J. Collins. 2003. Reverse engineering gene networks Integrating genetic perturbations with dynamical modeling. Proc Natl Acad Sci USA 100 5944-9. 

Liang, S., Ftrhrman, S., and Somogyi, R. (1998). REVEAL, a general reverse engineering algtmthm for irrference of genetic network architectures. Pacific Symp. Biocomput, 3 22. 

Koza, J.R., Mydlowec, W., Lanza, G., Yu, J. and Keane, M.A., 2000, Reverse Engineering and Automatic Synthesis of Metabolic Pathways from Observed Data Using Genetic Programming, SMI-2000-0851. 

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