Evolution of Feedback Loops in Oscillatory Systems

Feedback loops are major components of biochemical systems. Many systems show multiple such (positive or negative) feedback loops. Nevertheless, very few quantitative analyses address the question how such multiple feedback loops evolved. Based on published models from the mitotic cycle in embryogenesis, we build a few case studies. Using a simple core architecture (transcription, phosphorylation and degradation), we define oscillatory models having either one positive feedback or one negative feedback, or both loops. With these models, we address the following questions about evolvability: could a system evolve from a simple model to a more complex one with a continuous transition in the parameter space? How do new feedback loops emerge without disrupting the proper function of the system? Our results show that progressive formation of a second feedback loop is possible without disturbing existing oscillatory behavior. For this process, the parameters of the system have to change during evolution to maintain predefined properties of oscillations like period and amplitude.Comment: Proceedings of the 2009 FOSBE conference in Denver, CO, USA. 4 page

Information rate maximization over a resistive grid

The work presents the first results of the authors research on adaptive cellular neural networks (CNN) based on a global information theoretic cost-function. It considers the simplest case of optimizing a resistive grid such that the Shannon information rate across the input-output boundaries of the grid is maximized. Besides its importance in information theory, information rate has been proven to be a useful concept for principal as well independent component analysis (PCA, ICA). In contrast to linear fully connected neural networks, resistive grids due to their local coupling can resemble models of physical media and are feasible for a VLSI implementation. Results for spatially invariant as well as for the spatially variant case are presented and their relation to principal subspace analysis (PSA) is outlined. Simulation results show the validity of the proposed results

The Cramer-Rao Bound and DMT Signal Optimisation for the Identification of a Wiener-Type Model

In linear system identification, optimal excitation signals can be determined using the Cramer-Rao bound. This problem has not been thoroughly studied for the nonlinear case. In this work, the Cramer-Rao bound for a factorisable Volterra model is derived. The analytical result is supported with simulation examples. The bound is then used to find the optimal excitation signal out of the class of discrete multitone signals. As the model is nonlinear in the parameters, the bound depends on the model parameters themselves. On this basis, a three-step identification procedure is proposed. To illustrate the procedure, signal optimisation is explicitly performed for a third-order nonlinear model. Methods of nonlinear optimisation are applied for the parameter estimation of the model. As a baseline, the problem of optimal discrete multitone signals for linear FIR filter estimation is reviewed

Solving a Slick Problem; Morally Preferable; Objectors by Conscience

News release announces a UD biologist\u27s solutions for cleaning up the massive oil spill in the Persian golf, a senior research scientist\u27s comments on the use of smart weapons in the Persian Gulf, and counseling concerning the selective service law and legal option for members of the UD community will be offered

Semi-quantitative stability analysis constrains saturation levels in metabolic networks

Recently structural kinetic modeling has been proposed as an intermediary approach between a full kinetic descrip- tion of metabolic networks and a static constrained-based analysis of them. It extends the null-space analysis by a local stability analysis yielding a parametrization of the Jacobian in terms of saturation levels of the involved re- actions with respect to their substrate metabolite concen- tration. These levels are normalized and stay within well- defined bounds for every reaction. We utilize results from robust control theory to determine subintervals of satu- ration levels that render the steady state asymptotically stable. In particular we apply Kharitonov's theorem and parametric Lyapunov functions in conjunction with inter- val computation. A glycolytic pathway model comprising 12 reactions is used to illustrate the method

Co-Inventor of Jet Engine to Donate Draper Prize Medal to UD

News release announces that Hans von Ohain will present the Charles Stark Draper medal to the University of Dayton