> I don't have the time to fully deconstruct this paper, That's why you did not understand it. > but after a skim I'm left with the question, "so how does >

> I don't have the time to fully deconstruct this paper, That's why you did not understand it. > but after a skim I'm left with the question, "so how does > a single protein achieve non-linear response?" If you read the paper carefully (also the Supporting Information), you would see the origin of non-linearity. Transcription factors (TFs) bind to the operator and unbind from it. We make an assumption that this process of binding/unbinding is the fastest of all processes in the system. That is why we can describe it in a continuous way (so we do not consider TF single molecules, but their concentration, which is a continuous variable). Under such conditions, the transcription rate is a non-linear function of the the TF concentration. This is explained in the Supporting Information of the paper for the general case of n binding sites. Here I explain it in a more verbose way for the case of 2 binding sites: http://th.if.uj.edu.pl/~ochab/h.pdf http://th.if.uj.edu.pl/~ochab/h.pdf This non-linear function acts as a noise filter: If the TF concentrations across a cell population are not same, but given by a statistical distribution (one may call it "noise"), then the output distribution of transcription rates will be transformed in a counter-intuitive way. For example, a unimodal input distribution (of TFs) can be converted into a bimodal output distribution (of target proteins). So far, no one have found an analytical method of prediction, when the output distribution of proteins in a typical open-loop gene regulatory system will be bimodal. Even in the case of cooperative TF binding. Moreover, no one expected that bimodality can be found also in the case of non-cooperative TF binding. Which is kind of surprising, because the idea itself is simple. We did this. What is especially nice in our work is that the conditions for bimodality can be found without complicated calculations, only using a simple geometric construction that involves quantities that can be experimentally measured. > This paper seems to provide a mathematical model without > giving a good explanation for how it would be achieved in > nature. This is certainly not true. Please see the references, especially Friedman et al. PRL, Cai et al. Nature, Nevozhay et al. PNAS, Dublanche et al. Mol Syst Biol, and Taniguchi et al. Science. Best regards, Anna Ochab-Marcinek