This indicates that such models are good as prediction tools, but PLX-4720 purchase must be used with caution when investigating mechanisms of transcriptional regulation. There are further indications

that transcriptional modeling in the blastoderm is still in its infancy. All of the studies described above suffer from the fact that they do not yet represent the dynamics of gene regulation correctly, since the data they are fit to are not temporally resolved. Furthermore, data fits are often somewhat suboptimal. Finally, many of these models suffer from problems concerning their predictive power: in many cases parameter values cannot be estimated with confidence from the data. This was demonstrated by a rigorous analysis of parameter identifiability in two previously published models [87]. The first model considered in this study was able to predict quenching coefficients from models fits [84], but the analysis showed that conclusions drawn about the importance of co-operative transcription factor binding in another study [88] were not statistically well founded. All of these problems will have to be resolved, if we are to gain a rigorous quantitative understanding of the role of dynamic transcriptional

regulation in pattern formation. Up until very recently, modeling efforts in the Dorsomorphin nmr Drosophila blastoderm have focused on gene regulatory networks and their role in specifying positional information [ 15••]. The past few years, however, have seen an increasing shift of focus toward modeling the molecular mechanisms of transcriptional regulation and the biophysics of morphogen gradient formation. While the former efforts are still at an early stage, the latter have made impressive and rapid progress. In particular, the properties of the Bcd gradient have been described and

measured in great detail. These results are encouraging and exciting. However, we must remind ourselves that they are not sufficient to completely understand blastoderm pattern formation. A more holistic approach will be required that includes the complex regulatory interactions among morphogen targets. Phosphatidylethanolamine N-methyltransferase This poses a grand challenge for data-driven modeling. We must develop new methods and learn to think in different conceptual frameworks – such as that of non-linear systems theory – if we are to meet this challenge in the future. Papers of particular interest, published within the period of review, have been highlighted as: • of special interest “
“Current Opinion in Genetics & Development 2012, 22:553–561 This review comes from a themed issue on Genetics of system biology Edited by James Briscoe and James Sharpe For a complete overview see the Issue and the Editorial Available online 28th November 2012 0959-437X/$ – see front matter, © 2012 Elsevier Ltd. All rights reserved. http://dx.doi.org/10.1016/j.gde.