Reliability of genetic networks is evolvable

Control of the living cell functions with remarkable reliability despite the stochastic nature of the underlying molecular networks -- a property presumably optimized by biological evolution. We here ask to what extent the property of a stochastic dynamical network to produce reliable dynamics is an evolvable trait. Using an evolutionary algorithm based on a deterministic selection criterion for the reliability of dynamical attractors, we evolve dynamical networks of noisy discrete threshold nodes. We find that, starting from any random network, reliability of the attractor landscape can often be achieved with only few small changes to the network structure. Further, the evolvability of networks towards reliable dynamics while retaining their function is investigated and a high success rate is found.Comment: 5 pages, 3 figure

The C-Odd Four-Gluon State in the Color Glass Condensate

The study of the perturbative Odderon at high gluon densities in the color glass condensate requires to take into account states with more than three gluons. We formulate evolution equations for these states in which the number of gluons is not fixed during the evolution. We further determine the coupling of these Odderon states to the gamma to eta_c impact factor for arbitrary numbers of gluons. We find an exact solution of the evolution equation for the four-gluon Odderon state in terms of the three-gluon Odderon state. It is shown that a similar solution exists also for a different class of Odderon solutions which does not couple to the gamma to eta_c impact factor. We discuss the implications of our result from the perspective of constructing an effective field theory of reggeized gluons for the color glass condensate.Comment: 32 pages; v2: references, comments and one equation adde

Boolean network model predicts cell cycle sequence of fission yeast

A Boolean network model of the cell-cycle regulatory network of fission yeast (Schizosaccharomyces Pombe) is constructed solely on the basis of the known biochemical interaction topology. Simulating the model in the computer, faithfully reproduces the known sequence of regulatory activity patterns along the cell cycle of the living cell. Contrary to existing differential equation models, no parameters enter the model except the structure of the regulatory circuitry. The dynamical properties of the model indicate that the biological dynamical sequence is robustly implemented in the regulatory network, with the biological stationary state G1 corresponding to the dominant attractor in state space, and with the biological regulatory sequence being a strongly attractive trajectory. Comparing the fission yeast cell-cycle model to a similar model of the corresponding network in S. cerevisiae, a remarkable difference in circuitry, as well as dynamics is observed. While the latter operates in a strongly damped mode, driven by external excitation, the S. pombe network represents an auto-excited system with external damping.Comment: 10 pages, 3 figure

An Integrated Transcriptomic and Meta-Analysis of Hepatoma Cells Reveals Factors That Influence Susceptibility to HCV Infection

Hepatitis C virus (HCV) is a global problem. To better understand HCV infection researchers employ in vitro HCV cell-culture (HCVcc) systems that use Huh-7 derived hepatoma cells that are particularly permissive to HCV infection. A variety of hyper-permissive cells have been subcloned for this purpose. In addition, subclones of Huh-7 which have evolved resistance to HCV are available. However, the mechanisms of susceptibility or resistance to infection among these cells have not been fully determined. In order to elucidate mechanisms by which hepatoma cells are susceptible or resistant to HCV infection we performed genome-wide expression analyses of six Huh-7 derived cell cultures that have different levels of permissiveness to infection. A great number of genes, representing a wide spectrum of functions are differentially expressed between cells. To focus our investigation, we identify host proteins from HCV replicase complexes, perform gene expression analysis of three HCV infected cells and conduct a detailed analysis of differentially expressed host factors by integrating a variety of data sources. Our results demonstrate that changes relating to susceptibility to HCV infection in hepatoma cells are linked to the innate immune response, secreted signal peptides and host factors that have a role in virus entry and replication. This work identifies both known and novel host factors that may influence HCV infection. Our findings build upon current knowledge of the complex interplay between HCV and the host cell, which could aid development of new antiviral strategies