Controllability analysis and control synthesis for the ribosome flow   model
  The ribosomal density along the coding region of the mRNA molecule affect various fundamental intracellular phenomena including: protein production rates, organismal fitness, ribosomal drop off, and co-translational protein folding. Thus, regulating translation in order to obtain a desired ribosomal profile along the mRNA molecule is an important biological problem. We study this problem using a model for mRNA translation, called the ribosome flow model (RFM). In the RFM, the mRNA molecule is modeled as chain of n sites. The n state-variables describe the ribosomal density profile along the mRNA molecule, whereas the transition rates from each site to the next are controlled by n+1 positive constants. To study the problem of controlling the density profile, we consider some or all of the transition rates as time-varying controls. We consider the following problem: given an initial and a desired ribosomal density profile, determine the time-varying values of the transition rates that steer the RFM to this density profile, if they exist. Specifically, we consider two control problems. In the first, all transition rates can be regulated and the goal is to steer the ribosomal density profile and the protein production rate from a given initial value to a desired value. In the second, a single transition rate is controlled and the goal is to steer the production rate to a desired value. In the first case, we show that the system is controllable, i.e. the control is powerful enough to steer the RFM to any desired value, and we provide closed-form expressions for constant control functions (or transition rates) asymptotically steering the RFM to the desired value. For the second problem, we show that the production rate can be steered to any desired value in a feasible region determined by the other, constant transition rates. We discuss some of the biological implications of these results. 
Yoram Zarai and Michael Margaliot and Eduardo D. Sontag and Tamir   Tuller
q-bio.GN